CWE-770
AllowedAllocation of Resources Without Limits or Throttling
Abstraction: Base · Status: Incomplete
The product allocates a reusable resource or group of resources on behalf of an actor without imposing any intended restrictions on the size or number of resources that can be allocated.
3039 vulnerabilities reference this CWE, most recent first.
GHSA-2WPX-QPW2-G5H5
Vulnerability from github – Published: 2026-04-28 22:40 – Updated: 2026-05-08 15:27Summary
CoreDNS' DNS-over-QUIC (DoQ) server can be driven into large goroutine and memory growth by a remote client that opens many QUIC streams and stalls after sending only 1 byte. Even with a small configured quic { worker_pool_size ... }, CoreDNS still spawns a goroutine per accepted stream (workers + waiters) and active workers can block indefinitely in io.ReadFull() with no per-stream read deadline, enabling unauthenticated remote DoS via memory exhaustion/OOM-kill.
Details
CoreDNS' DoQ server uses a global worker pool (streamProcessPool) to limit concurrent stream processing, but when the pool is full it still spawns a goroutine per accepted stream that waits to acquire a worker token: select { case s.streamProcessPool <- ...: go ...; default: go ... wait for token ... } (core/dnsserver/server_quic.go)
Additionally, the DoQ message framing reads are blocking io.ReadFull() calls with no per-stream read deadline: readDOQMessage() reads the 2-byte length prefix and message body via io.ReadFull() (core/dnsserver/server_quic.go)
This allows an attacker to pin all workers by sending 1 byte (so io.ReadFull() blocks waiting for the second byte of the DoQ length prefix), while also creating an unbounded backlog of goroutines waiting for a worker token.
Note: this appears to be a result of an incomplete fix/regression for CVE-2025-47950 (GHSA-cvx7-x8pj-x2gw).
PoC
- Adjust COREDNS_BIN in the PoC to point at right path (see the top-level const definitions for tunables as well)
- Run python3 ./doq-dos-repro.py
- Expected sample output: *** Start CoreDNS *** Corefile: /tmp/vh-f003-doq-mem-regression/Corefile Log: /tmp/vh-f003-doq-mem-regression/coredns.log
*** Baseline sample (idle) *** rss_kib=49380 go_goroutines=17
*** Build + run partial-stream flooder *** go: downloading golang.org/x/net v0.43.0 go: downloading golang.org/x/crypto v0.41.0 go: downloading go.uber.org/mock v0.5.2 go: downloading github.com/stretchr/testify v1.11.1 go: downloading golang.org/x/sys v0.35.0 go: downloading github.com/pmezard/go-difflib v1.0.0 go: downloading github.com/davecgh/go-spew v1.1.1 go: downloading gopkg.in/yaml.v3 v3.0.1
*** Candidate sample (during attack) *** rss_kib=137968 go_goroutines=15557
*** Flooder output *** opened conns=60 streams_per_conn=256 total_streams=15360
*** Wrote results *** /tmp/vh-f003-doq-mem-regression/results.json
*** OK *** DoQ flood caused goroutine/RSS growth despite worker_pool_size.
Impact
Unauthenticated remote DoS on an encrypted DNS transport via goroutine/RSS growth leading to OOM-kill/crash and service outage.
{
"affected": [
{
"package": {
"ecosystem": "Go",
"name": "github.com/coredns/coredns"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "1.14.3"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-32934"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2026-04-28T22:40:38Z",
"nvd_published_at": "2026-05-05T20:16:35Z",
"severity": "HIGH"
},
"details": "### Summary\nCoreDNS\u0027 DNS-over-QUIC (DoQ) server can be driven into large goroutine and memory growth by a remote client that opens many QUIC streams and stalls after sending only 1 byte. Even with a small configured quic { worker_pool_size ... }, CoreDNS still spawns a goroutine per accepted stream (workers + waiters) and active workers can block indefinitely in io.ReadFull() with no per-stream read deadline, enabling unauthenticated remote DoS via memory exhaustion/OOM-kill.\n\n### Details\nCoreDNS\u0027 DoQ server uses a global worker pool (streamProcessPool) to limit concurrent stream processing, but when the pool is full it still spawns a goroutine per accepted stream that waits to acquire a worker token: select { case s.streamProcessPool \u003c- ...: go ...; default: go ... wait for token ... } (core/dnsserver/server_quic.go)\n\nAdditionally, the DoQ message framing reads are blocking io.ReadFull() calls with no per-stream read deadline: readDOQMessage() reads the 2-byte length prefix and message body via io.ReadFull() (core/dnsserver/server_quic.go)\n\nThis allows an attacker to pin all workers by sending 1 byte (so io.ReadFull() blocks waiting for the second byte of the DoQ length prefix), while also creating an unbounded backlog of goroutines waiting for a worker token.\n\nNote: this appears to be a result of an incomplete fix/regression for CVE-2025-47950 (GHSA-cvx7-x8pj-x2gw).\n\n### PoC\n1. Adjust COREDNS_BIN in the PoC to point at right path (see the top-level const definitions for tunables as well)\n2. Run python3 ./doq-dos-repro.py\n3. Expected sample output:\n*** Start CoreDNS ***\nCorefile: /tmp/vh-f003-doq-mem-regression/Corefile\nLog: /tmp/vh-f003-doq-mem-regression/coredns.log\n\n*** Baseline sample (idle) ***\nrss_kib=49380 go_goroutines=17\n\n*** Build + run partial-stream flooder ***\ngo: downloading golang.org/x/net v0.43.0\ngo: downloading golang.org/x/crypto v0.41.0\ngo: downloading go.uber.org/mock v0.5.2\ngo: downloading github.com/stretchr/testify v1.11.1\ngo: downloading golang.org/x/sys v0.35.0\ngo: downloading github.com/pmezard/go-difflib v1.0.0\ngo: downloading github.com/davecgh/go-spew v1.1.1\ngo: downloading gopkg.in/yaml.v3 v3.0.1\n\n*** Candidate sample (during attack) ***\nrss_kib=137968 go_goroutines=15557\n\n*** Flooder output ***\nopened conns=60 streams_per_conn=256 total_streams=15360\n\n*** Wrote results ***\n/tmp/vh-f003-doq-mem-regression/results.json\n\n*** OK ***\nDoQ flood caused goroutine/RSS growth despite worker_pool_size.\n\n\n### Impact\nUnauthenticated remote DoS on an encrypted DNS transport via goroutine/RSS growth leading to OOM-kill/crash and service outage.",
"id": "GHSA-2wpx-qpw2-g5h5",
"modified": "2026-05-08T15:27:59Z",
"published": "2026-04-28T22:40:38Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/coredns/coredns/security/advisories/GHSA-2wpx-qpw2-g5h5"
},
{
"type": "WEB",
"url": "https://github.com/coredns/coredns/security/advisories/GHSA-cvx7-x8pj-x2gw"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-32934"
},
{
"type": "PACKAGE",
"url": "https://github.com/coredns/coredns"
},
{
"type": "WEB",
"url": "https://github.com/coredns/coredns/releases/tag/v1.14.3"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "CoreDNS\u0027 DoQ worker pool does not bound stream backlog"
}
GHSA-2WQM-G7M4-4GJ8
Vulnerability from github – Published: 2022-04-30 18:17 – Updated: 2022-04-30 18:17iptables before 1.2.4 does not accurately convert rate limits that are specified on the command line, which could allow attackers or users to generate more or less traffic than intended by the administrator.
{
"affected": [],
"aliases": [
"CVE-2001-1388"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2001-11-05T05:00:00Z",
"severity": "MODERATE"
},
"details": "iptables before 1.2.4 does not accurately convert rate limits that are specified on the command line, which could allow attackers or users to generate more or less traffic than intended by the administrator.",
"id": "GHSA-2wqm-g7m4-4gj8",
"modified": "2022-04-30T18:17:55Z",
"published": "2022-04-30T18:17:55Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2001-1388"
},
{
"type": "WEB",
"url": "http://bugzilla.redhat.com/bugzilla/show_bug.cgi?id=53325"
},
{
"type": "WEB",
"url": "http://rhn.redhat.com/errata/RHSA-2001-144.html"
}
],
"schema_version": "1.4.0",
"severity": []
}
GHSA-2WV3-4CG3-63G8
Vulnerability from github – Published: 2024-04-02 09:30 – Updated: 2024-04-02 09:30in OpenHarmony v3.2.4 and prior versions allow a local attacker cause DOS through stack overflow.
{
"affected": [],
"aliases": [
"CVE-2024-29086"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2024-04-02T07:15:45Z",
"severity": "LOW"
},
"details": "in OpenHarmony v3.2.4 and prior versions allow a local attacker cause DOS through stack overflow.",
"id": "GHSA-2wv3-4cg3-63g8",
"modified": "2024-04-02T09:30:42Z",
"published": "2024-04-02T09:30:42Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2024-29086"
},
{
"type": "WEB",
"url": "https://gitee.com/openharmony/security/blob/master/zh/security-disclosure/2024/2024-04.md"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L",
"type": "CVSS_V3"
}
]
}
GHSA-2WX7-J39G-4P6G
Vulnerability from github – Published: 2025-03-12 18:32 – Updated: 2025-03-12 18:32A vulnerability in the handling of specific packets that are punted from a line card to a route processor in Cisco IOS XR Software Release 7.9.2 could allow an unauthenticated, adjacent attacker to cause control plane traffic to stop working on multiple Cisco IOS XR platforms.
This vulnerability is due to incorrect handling of packets that are punted to the route processor. An attacker could exploit this vulnerability by sending traffic, which must be handled by the Linux stack on the route processor, to an affected device. A successful exploit could allow the attacker to cause control plane traffic to stop working, resulting in a denial of service (DoS) condition.
{
"affected": [],
"aliases": [
"CVE-2025-20141"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2025-03-12T16:15:21Z",
"severity": "HIGH"
},
"details": "A vulnerability in the handling of specific packets that are punted from a line card to a route processor in Cisco IOS XR Software Release 7.9.2 could allow an unauthenticated, adjacent attacker to cause control plane traffic to stop working on multiple Cisco IOS XR platforms.\u0026nbsp;\n\nThis vulnerability is due to incorrect handling of packets that are punted to the route processor. An attacker could exploit this vulnerability by sending traffic, which must be handled by the Linux stack on the route processor, to an affected device. A successful exploit could allow the attacker to cause control plane traffic to stop working, resulting in a denial of service (DoS) condition.",
"id": "GHSA-2wx7-j39g-4p6g",
"modified": "2025-03-12T18:32:52Z",
"published": "2025-03-12T18:32:52Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-20141"
},
{
"type": "WEB",
"url": "https://blog.apnic.net/2024/09/02/crafting-endless-as-paths-in-bgp"
},
{
"type": "WEB",
"url": "https://sec.cloudapps.cisco.com/security/center/content/CiscoSecurityAdvisory/cisco-sa-xr792-bWfVDPY"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:A/AC:L/PR:N/UI:N/S:C/C:N/I:N/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-2WXF-96VC-52R7
Vulnerability from github – Published: 2026-02-03 18:30 – Updated: 2026-02-04 18:30An issue was discovered in the Wi-Fi driver in Samsung Mobile Processor and Wearable Processor Exynos 980, 850, 1080, 1280, 2200, 1330, 1380, 1480, 1580, W920, W930, and W1000. There is unbounded memory allocation via a large buffer in a /proc/driver/unifi0/p2p_certif write operation, leading to kernel memory exhaustion.
{
"affected": [],
"aliases": [
"CVE-2025-58347"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-02-03T18:16:14Z",
"severity": "MODERATE"
},
"details": "An issue was discovered in the Wi-Fi driver in Samsung Mobile Processor and Wearable Processor Exynos 980, 850, 1080, 1280, 2200, 1330, 1380, 1480, 1580, W920, W930, and W1000. There is unbounded memory allocation via a large buffer in a /proc/driver/unifi0/p2p_certif write operation, leading to kernel memory exhaustion.",
"id": "GHSA-2wxf-96vc-52r7",
"modified": "2026-02-04T18:30:30Z",
"published": "2026-02-03T18:30:46Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-58347"
},
{
"type": "WEB",
"url": "https://semiconductor.samsung.com/support/quality-support/product-security-updates"
},
{
"type": "WEB",
"url": "https://semiconductor.samsung.com/support/quality-support/product-security-updates/cve-2025-58347"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-2XGV-5CV2-47VV
Vulnerability from github – Published: 2026-04-10 19:23 – Updated: 2026-04-10 19:23Summary
The WSGI-based recipe registry server (server.py) reads the entire HTTP request body into memory based on the client-supplied Content-Length header with no upper bound. Combined with authentication being disabled by default (no token configured), any local process can send arbitrarily large POST requests to exhaust server memory and cause a denial of service. The Starlette-based server (serve.py) has RequestSizeLimitMiddleware with a 10MB limit, but the WSGI server lacks any equivalent protection.
Details
The vulnerable code path in src/praisonai/praisonai/recipe/server.py:
1. No size limit on body read (line 551-555):
content_length = int(environ.get("CONTENT_LENGTH", 0))
body = environ["wsgi.input"].read(content_length) if content_length > 0 else b""
The content_length is taken directly from the HTTP header with no maximum check. The entire body is read into a single bytes object in memory.
2. Second in-memory copy via multipart parsing (line 169-172):
result = {"fields": {}, "files": {}}
boundary_bytes = f"--{boundary}".encode()
parts = body.split(boundary_bytes)
The _parse_multipart method splits the already-buffered body and stores file contents in a dict, creating additional in-memory copies.
3. Third copy to temp file (line 420-421):
with tempfile.NamedTemporaryFile(suffix=".praison", delete=False) as tmp:
tmp.write(bundle_content)
The bundle content is then written to disk and persisted in the registry, also without size checks.
4. Authentication disabled by default (line 91-94):
def _check_auth(self, headers: Dict[str, str]) -> bool:
if not self.token:
return True # No token configured = no auth
The self.token defaults to None unless PRAISONAI_REGISTRY_TOKEN is set or --token is passed on the CLI.
The entry point is praisonai registry serve (cli/features/registry.py:176), which calls run_server() binding to 127.0.0.1:7777 by default.
In contrast, serve.py (the Starlette server) has RequestSizeLimitMiddleware at line 725-732 enforcing a 10MB default limit. The WSGI server has no equivalent.
PoC
# Start the registry server with default settings (no auth, localhost)
praisonai registry serve &
# Step 1: Create a large bundle (~500MB)
mkdir -p /tmp/dos-test
echo '{"name":"dos","version":"1.0.0"}' > /tmp/dos-test/manifest.json
dd if=/dev/zero of=/tmp/dos-test/pad bs=1M count=500
tar czf /tmp/dos-bundle.praison -C /tmp/dos-test .
# Step 2: Upload — server buffers ~500MB into RAM with no limit
curl -X POST http://127.0.0.1:7777/v1/recipes/dos/1.0.0 \
-F 'bundle=@/tmp/dos-bundle.praison' -F 'force=true'
# Step 3: Repeat to exhaust memory
for v in 1.0.{1..10}; do
curl -X POST http://127.0.0.1:7777/v1/recipes/dos/$v \
-F 'bundle=@/tmp/dos-bundle.praison' &
done
# Server process will be OOM-killed
Impact
- Memory exhaustion: A single large request can consume all available memory, crashing the server process (and potentially other processes via OOM killer).
- Disk exhaustion: Repeated uploads persist bundles to disk at
~/.praison/registry/with no quota, potentially filling the filesystem. - No authentication barrier: Default configuration requires no token, so any local process (including via SSRF from other services on the same host) can trigger this.
- Availability impact: The registry server becomes unavailable, blocking recipe publish/download operations.
The default bind address of 127.0.0.1 limits exploitability to local attackers or SSRF scenarios. If a user binds to 0.0.0.0 (common for shared environments or containers), the attack surface extends to the network.
Recommended Fix
Add a request size limit to the WSGI application, consistent with serve.py's 10MB default:
# In create_wsgi_app(), before reading the body:
MAX_REQUEST_SIZE = 10 * 1024 * 1024 # 10MB, matching serve.py
def application(environ, start_response):
# ... existing code ...
# Read body with size limit
try:
content_length = int(environ.get("CONTENT_LENGTH", 0))
except (ValueError, TypeError):
content_length = 0
if content_length > MAX_REQUEST_SIZE:
status = "413 Request Entity Too Large"
response_headers = [("Content-Type", "application/json")]
body = json.dumps({
"error": {
"code": "request_too_large",
"message": f"Request body too large. Max: {MAX_REQUEST_SIZE} bytes"
}
}).encode()
start_response(status, response_headers)
return [body]
body = environ["wsgi.input"].read(content_length) if content_length > 0 else b""
# ... rest of handler ...
Additionally, consider:
- Adding a --max-request-size CLI flag to praisonai registry serve
- Adding per-recipe disk quota enforcement in LocalRegistry.publish()
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "PraisonAI"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "4.5.128"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-40115"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2026-04-10T19:23:13Z",
"nvd_published_at": "2026-04-09T22:16:35Z",
"severity": "MODERATE"
},
"details": "## Summary\n\nThe WSGI-based recipe registry server (`server.py`) reads the entire HTTP request body into memory based on the client-supplied `Content-Length` header with no upper bound. Combined with authentication being disabled by default (no token configured), any local process can send arbitrarily large POST requests to exhaust server memory and cause a denial of service. The Starlette-based server (`serve.py`) has `RequestSizeLimitMiddleware` with a 10MB limit, but the WSGI server lacks any equivalent protection.\n\n## Details\n\nThe vulnerable code path in `src/praisonai/praisonai/recipe/server.py`:\n\n**1. No size limit on body read (line 551-555):**\n```python\ncontent_length = int(environ.get(\"CONTENT_LENGTH\", 0))\nbody = environ[\"wsgi.input\"].read(content_length) if content_length \u003e 0 else b\"\"\n```\n\nThe `content_length` is taken directly from the HTTP header with no maximum check. The entire body is read into a single `bytes` object in memory.\n\n**2. Second in-memory copy via multipart parsing (line 169-172):**\n```python\nresult = {\"fields\": {}, \"files\": {}}\nboundary_bytes = f\"--{boundary}\".encode()\nparts = body.split(boundary_bytes)\n```\n\nThe `_parse_multipart` method splits the already-buffered body and stores file contents in a dict, creating additional in-memory copies.\n\n**3. Third copy to temp file (line 420-421):**\n```python\nwith tempfile.NamedTemporaryFile(suffix=\".praison\", delete=False) as tmp:\n tmp.write(bundle_content)\n```\n\nThe bundle content is then written to disk and persisted in the registry, also without size checks.\n\n**4. Authentication disabled by default (line 91-94):**\n```python\ndef _check_auth(self, headers: Dict[str, str]) -\u003e bool:\n if not self.token:\n return True # No token configured = no auth\n```\n\nThe `self.token` defaults to `None` unless `PRAISONAI_REGISTRY_TOKEN` is set or `--token` is passed on the CLI.\n\nThe entry point is `praisonai registry serve` (cli/features/registry.py:176), which calls `run_server()` binding to `127.0.0.1:7777` by default.\n\nIn contrast, `serve.py` (the Starlette server) has `RequestSizeLimitMiddleware` at line 725-732 enforcing a 10MB default limit. The WSGI server has no equivalent.\n\n## PoC\n\n```bash\n# Start the registry server with default settings (no auth, localhost)\npraisonai registry serve \u0026\n\n# Step 1: Create a large bundle (~500MB)\nmkdir -p /tmp/dos-test\necho \u0027{\"name\":\"dos\",\"version\":\"1.0.0\"}\u0027 \u003e /tmp/dos-test/manifest.json\ndd if=/dev/zero of=/tmp/dos-test/pad bs=1M count=500\ntar czf /tmp/dos-bundle.praison -C /tmp/dos-test .\n\n# Step 2: Upload \u2014 server buffers ~500MB into RAM with no limit\ncurl -X POST http://127.0.0.1:7777/v1/recipes/dos/1.0.0 \\\n -F \u0027bundle=@/tmp/dos-bundle.praison\u0027 -F \u0027force=true\u0027\n\n# Step 3: Repeat to exhaust memory\nfor v in 1.0.{1..10}; do\n curl -X POST http://127.0.0.1:7777/v1/recipes/dos/$v \\\n -F \u0027bundle=@/tmp/dos-bundle.praison\u0027 \u0026\ndone\n# Server process will be OOM-killed\n```\n\n## Impact\n\n- **Memory exhaustion**: A single large request can consume all available memory, crashing the server process (and potentially other processes via OOM killer).\n- **Disk exhaustion**: Repeated uploads persist bundles to disk at `~/.praison/registry/` with no quota, potentially filling the filesystem.\n- **No authentication barrier**: Default configuration requires no token, so any local process (including via SSRF from other services on the same host) can trigger this.\n- **Availability impact**: The registry server becomes unavailable, blocking recipe publish/download operations.\n\nThe default bind address of `127.0.0.1` limits exploitability to local attackers or SSRF scenarios. If a user binds to `0.0.0.0` (common for shared environments or containers), the attack surface extends to the network.\n\n## Recommended Fix\n\nAdd a request size limit to the WSGI application, consistent with `serve.py`\u0027s 10MB default:\n\n```python\n# In create_wsgi_app(), before reading the body:\nMAX_REQUEST_SIZE = 10 * 1024 * 1024 # 10MB, matching serve.py\n\ndef application(environ, start_response):\n # ... existing code ...\n \n # Read body with size limit\n try:\n content_length = int(environ.get(\"CONTENT_LENGTH\", 0))\n except (ValueError, TypeError):\n content_length = 0\n \n if content_length \u003e MAX_REQUEST_SIZE:\n status = \"413 Request Entity Too Large\"\n response_headers = [(\"Content-Type\", \"application/json\")]\n body = json.dumps({\n \"error\": {\n \"code\": \"request_too_large\",\n \"message\": f\"Request body too large. Max: {MAX_REQUEST_SIZE} bytes\"\n }\n }).encode()\n start_response(status, response_headers)\n return [body]\n \n body = environ[\"wsgi.input\"].read(content_length) if content_length \u003e 0 else b\"\"\n # ... rest of handler ...\n```\n\nAdditionally, consider:\n- Adding a `--max-request-size` CLI flag to `praisonai registry serve`\n- Adding per-recipe disk quota enforcement in `LocalRegistry.publish()`",
"id": "GHSA-2xgv-5cv2-47vv",
"modified": "2026-04-10T19:23:13Z",
"published": "2026-04-10T19:23:13Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/MervinPraison/PraisonAI/security/advisories/GHSA-2xgv-5cv2-47vv"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-40115"
},
{
"type": "PACKAGE",
"url": "https://github.com/MervinPraison/PraisonAI"
},
{
"type": "WEB",
"url": "https://github.com/MervinPraison/PraisonAI/releases/tag/v4.5.128"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
],
"summary": "PraisonAI has Unrestricted Upload Size in WSGI Recipe Registry Server that Enables Memory Exhaustion DoS"
}
GHSA-2XPX-VCMQ-5F72
Vulnerability from github – Published: 2024-06-28 21:05 – Updated: 2024-07-02 02:26Summary
Missing limit for accepted NTS-KE connections allows an unauthenticated remote attacker to crash ntpd-rs when an NTS-KE server is configured. Non NTS-KE server configurations, such as the default ntpd-rs configuration, are unaffected.
Details
Operating systems have a limit for the number of open file descriptors (which includes sockets) in a single process, e.g. 1024 on Linux by default. When ntpd-rs is configured as an NTS server, it accepts TCP connections for the NTS-KE service. If the process has reached the descriptor limit and tries to accept a new TCP connection, the accept() system call will return with the EMFILE error and cause ntpd-rs to abort.
A remote attacker can open a large number of parallel TCP connections to the server to trigger this crash. The connections need to be opened quickly enough to avoid the key-exchange-timeout-ms timeout (by default 1000 milliseconds).
Impact
Only NTS-KE server configuration are affected. Those without an NTS-KE server configuration such as NTS client only or NTP only configuration are unaffected. For affected configurations the ntpd-rs daemon can made completely unavailable by crashing the service. If ntpd-rs is automatically restarted, an attacker can repeat the attack to prevent ntpd-rs from doing anything useful.
Workarounds
- Disable NTS-KE server functionality
- Increase system resource limits (
RLIMIT_NOFILE) to make the attack more difficult - Lower the
key-exchange-timeout-msconfiguration setting to make the attack more difficult
{
"affected": [
{
"database_specific": {
"last_known_affected_version_range": "\u003c= 1.1.2"
},
"package": {
"ecosystem": "crates.io",
"name": "ntpd"
},
"ranges": [
{
"events": [
{
"introduced": "0.3.1"
},
{
"fixed": "1.1.3"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2024-38528"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2024-06-28T21:05:52Z",
"nvd_published_at": "2024-06-28T20:15:02Z",
"severity": "HIGH"
},
"details": "### Summary\nMissing limit for accepted NTS-KE connections allows an unauthenticated remote attacker to crash ntpd-rs when an NTS-KE server is configured. Non NTS-KE server configurations, such as the default ntpd-rs configuration, are unaffected.\n\n### Details\nOperating systems have a limit for the number of open file descriptors (which includes sockets) in a single process, e.g. 1024 on Linux by default. When ntpd-rs is configured as an NTS server, it accepts TCP connections for the NTS-KE service. If the process has reached the descriptor limit and tries to accept a new TCP connection, the accept() system call will return with the EMFILE error and cause ntpd-rs to abort.\n\nA remote attacker can open a large number of parallel TCP connections to the server to trigger this crash. The connections need to be opened quickly enough to avoid the `key-exchange-timeout-ms` timeout (by default 1000 milliseconds).\n\n### Impact\nOnly NTS-KE server configuration are affected. Those without an NTS-KE server configuration such as NTS client only or NTP only configuration are unaffected. For affected configurations the ntpd-rs daemon can made completely unavailable by crashing the service. If ntpd-rs is automatically restarted, an attacker can repeat the attack to prevent ntpd-rs from doing anything useful.\n\n### Workarounds\n- Disable NTS-KE server functionality\n- Increase system resource limits (`RLIMIT_NOFILE`) to make the attack more difficult\n- Lower the `key-exchange-timeout-ms` configuration setting to make the attack more difficult",
"id": "GHSA-2xpx-vcmq-5f72",
"modified": "2024-07-02T02:26:15Z",
"published": "2024-06-28T21:05:52Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/pendulum-project/ntpd-rs/security/advisories/GHSA-2xpx-vcmq-5f72"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2024-38528"
},
{
"type": "WEB",
"url": "https://github.com/pendulum-project/ntpd-rs/commit/6049687006ea5b26eeac927964b5fcc80d7bde50"
},
{
"type": "PACKAGE",
"url": "https://github.com/pendulum-project/ntpd-rs"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Unlimited number of NTS-KE connections can crash ntpd-rs server"
}
GHSA-2XW3-M2WF-5R5M
Vulnerability from github – Published: 2026-01-07 18:30 – Updated: 2026-01-07 18:30In Aris v10.0.23.0.3587512 and before, the file upload functionality does not enforce any rate limiting or throttling, allowing users to upload files at an unrestricted rate. An attacker can exploit this behavior to rapidly upload a large volume of files, potentially leading to resource exhaustion such as disk space depletion, increased server load, or degraded performance
{
"affected": [],
"aliases": [
"CVE-2025-66838"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-01-07T16:15:51Z",
"severity": "MODERATE"
},
"details": "In Aris v10.0.23.0.3587512 and before, the file upload functionality does not enforce any rate limiting or throttling, allowing users to upload files at an unrestricted rate. An attacker can exploit this behavior to rapidly upload a large volume of files, potentially leading to resource exhaustion such as disk space depletion, increased server load, or degraded performance",
"id": "GHSA-2xw3-m2wf-5r5m",
"modified": "2026-01-07T18:30:25Z",
"published": "2026-01-07T18:30:25Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-66838"
},
{
"type": "WEB",
"url": "https://github.com/saykino/CVE-2025-66838"
},
{
"type": "WEB",
"url": "https://www.softwareag.com"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-2XWM-F2V4-92VH
Vulnerability from github – Published: 2023-02-12 06:30 – Updated: 2023-02-21 18:30Transient DOS due to uncontrolled resource consumption in WLAN firmware when peer is freed in non qos state.
{
"affected": [],
"aliases": [
"CVE-2022-40513"
],
"database_specific": {
"cwe_ids": [
"CWE-400",
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2023-02-12T04:15:00Z",
"severity": "HIGH"
},
"details": "Transient DOS due to uncontrolled resource consumption in WLAN firmware when peer is freed in non qos state.",
"id": "GHSA-2xwm-f2v4-92vh",
"modified": "2023-02-21T18:30:17Z",
"published": "2023-02-12T06:30:29Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2022-40513"
},
{
"type": "WEB",
"url": "https://www.qualcomm.com/company/product-security/bulletins/february-2023-bulletin"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-326P-894X-J8C7
Vulnerability from github – Published: 2023-11-01 15:33 – Updated: 2023-11-01 15:33A regression was introduced in the Red Hat build of python-eventlet due to a change in the patch application strategy, resulting in a patch for CVE-2021-21419 not being applied for all builds of all products.
{
"affected": [],
"aliases": [
"CVE-2023-5625"
],
"database_specific": {
"cwe_ids": [
"CWE-400",
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2023-11-01T14:15:38Z",
"severity": "MODERATE"
},
"details": "A regression was introduced in the Red Hat build of python-eventlet due to a change in the patch application strategy, resulting in a patch for CVE-2021-21419 not being applied for all builds of all products.",
"id": "GHSA-326p-894x-j8c7",
"modified": "2023-11-01T15:33:29Z",
"published": "2023-11-01T15:33:29Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2023-5625"
},
{
"type": "WEB",
"url": "https://access.redhat.com/errata/RHSA-2023:6128"
},
{
"type": "WEB",
"url": "https://access.redhat.com/errata/RHSA-2024:0188"
},
{
"type": "WEB",
"url": "https://access.redhat.com/errata/RHSA-2024:0213"
},
{
"type": "WEB",
"url": "https://access.redhat.com/security/cve/CVE-2023-5625"
},
{
"type": "WEB",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2244717"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L",
"type": "CVSS_V3"
}
]
}
Mitigation
Clearly specify the minimum and maximum expectations for capabilities, and dictate which behaviors are acceptable when resource allocation reaches limits.
Mitigation
Limit the amount of resources that are accessible to unprivileged users. Set per-user limits for resources. Allow the system administrator to define these limits. Be careful to avoid CWE-410.
Mitigation
Design throttling mechanisms into the system architecture. The best protection is to limit the amount of resources that an unauthorized user can cause to be expended. A strong authentication and access control model will help prevent such attacks from occurring in the first place, and it will help the administrator to identify who is committing the abuse. The login application should be protected against DoS attacks as much as possible. Limiting the database access, perhaps by caching result sets, can help minimize the resources expended. To further limit the potential for a DoS attack, consider tracking the rate of requests received from users and blocking requests that exceed a defined rate threshold.
Mitigation MIT-5
Strategy: Input Validation
- Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does.
- When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue."
- Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright.
Mitigation MIT-15
For any security checks that are performed on the client side, ensure that these checks are duplicated on the server side, in order to avoid CWE-602. Attackers can bypass the client-side checks by modifying values after the checks have been performed, or by changing the client to remove the client-side checks entirely. Then, these modified values would be submitted to the server.
Mitigation
- Mitigation of resource exhaustion attacks requires that the target system either:
- The first of these solutions is an issue in itself though, since it may allow attackers to prevent the use of the system by a particular valid user. If the attacker impersonates the valid user, they may be able to prevent the user from accessing the server in question.
- The second solution can be difficult to effectively institute -- and even when properly done, it does not provide a full solution. It simply requires more resources on the part of the attacker.
- recognizes the attack and denies that user further access for a given amount of time, typically by using increasing time delays
- uniformly throttles all requests in order to make it more difficult to consume resources more quickly than they can again be freed.
Mitigation
Ensure that protocols have specific limits of scale placed on them.
Mitigation MIT-38.1
- If the program must fail, ensure that it fails gracefully (fails closed). There may be a temptation to simply let the program fail poorly in cases such as low memory conditions, but an attacker may be able to assert control before the software has fully exited. Alternately, an uncontrolled failure could cause cascading problems with other downstream components; for example, the program could send a signal to a downstream process so the process immediately knows that a problem has occurred and has a better chance of recovery.
- Ensure that all failures in resource allocation place the system into a safe posture.
Mitigation MIT-47
Strategy: Resource Limitation
- Use quotas or other resource-limiting settings provided by the operating system or environment. For example, when managing system resources in POSIX, setrlimit() can be used to set limits for certain types of resources, and getrlimit() can determine how many resources are available. However, these functions are not available on all operating systems.
- When the current levels get close to the maximum that is defined for the application (see CWE-770), then limit the allocation of further resources to privileged users; alternately, begin releasing resources for less-privileged users. While this mitigation may protect the system from attack, it will not necessarily stop attackers from adversely impacting other users.
- Ensure that the application performs the appropriate error checks and error handling in case resources become unavailable (CWE-703).
CAPEC-125: Flooding
An adversary consumes the resources of a target by rapidly engaging in a large number of interactions with the target. This type of attack generally exposes a weakness in rate limiting or flow. When successful this attack prevents legitimate users from accessing the service and can cause the target to crash. This attack differs from resource depletion through leaks or allocations in that the latter attacks do not rely on the volume of requests made to the target but instead focus on manipulation of the target's operations. The key factor in a flooding attack is the number of requests the adversary can make in a given period of time. The greater this number, the more likely an attack is to succeed against a given target.
CAPEC-130: Excessive Allocation
An adversary causes the target to allocate excessive resources to servicing the attackers' request, thereby reducing the resources available for legitimate services and degrading or denying services. Usually, this attack focuses on memory allocation, but any finite resource on the target could be the attacked, including bandwidth, processing cycles, or other resources. This attack does not attempt to force this allocation through a large number of requests (that would be Resource Depletion through Flooding) but instead uses one or a small number of requests that are carefully formatted to force the target to allocate excessive resources to service this request(s). Often this attack takes advantage of a bug in the target to cause the target to allocate resources vastly beyond what would be needed for a normal request.
CAPEC-147: XML Ping of the Death
An attacker initiates a resource depletion attack where a large number of small XML messages are delivered at a sufficiently rapid rate to cause a denial of service or crash of the target. Transactions such as repetitive SOAP transactions can deplete resources faster than a simple flooding attack because of the additional resources used by the SOAP protocol and the resources necessary to process SOAP messages. The transactions used are immaterial as long as they cause resource utilization on the target. In other words, this is a normal flooding attack augmented by using messages that will require extra processing on the target.
CAPEC-197: Exponential Data Expansion
An adversary submits data to a target application which contains nested exponential data expansion to produce excessively large output. Many data format languages allow the definition of macro-like structures that can be used to simplify the creation of complex structures. However, this capability can be abused to create excessive demands on a processor's CPU and memory. A small number of nested expansions can result in an exponential growth in demands on memory.
CAPEC-229: Serialized Data Parameter Blowup
This attack exploits certain serialized data parsers (e.g., XML, YAML, etc.) which manage data in an inefficient manner. The attacker crafts an serialized data file with multiple configuration parameters in the same dataset. In a vulnerable parser, this results in a denial of service condition where CPU resources are exhausted because of the parsing algorithm. The weakness being exploited is tied to parser implementation and not language specific.
CAPEC-230: Serialized Data with Nested Payloads
Applications often need to transform data in and out of a data format (e.g., XML and YAML) by using a parser. It may be possible for an adversary to inject data that may have an adverse effect on the parser when it is being processed. Many data format languages allow the definition of macro-like structures that can be used to simplify the creation of complex structures. By nesting these structures, causing the data to be repeatedly substituted, an adversary can cause the parser to consume more resources while processing, causing excessive memory consumption and CPU utilization.
CAPEC-231: Oversized Serialized Data Payloads
An adversary injects oversized serialized data payloads into a parser during data processing to produce adverse effects upon the parser such as exhausting system resources and arbitrary code execution.
CAPEC-469: HTTP DoS
An attacker performs flooding at the HTTP level to bring down only a particular web application rather than anything listening on a TCP/IP connection. This denial of service attack requires substantially fewer packets to be sent which makes DoS harder to detect. This is an equivalent of SYN flood in HTTP. The idea is to keep the HTTP session alive indefinitely and then repeat that hundreds of times. This attack targets resource depletion weaknesses in web server software. The web server will wait to attacker's responses on the initiated HTTP sessions while the connection threads are being exhausted.
CAPEC-482: TCP Flood
An adversary may execute a flooding attack using the TCP protocol with the intent to deny legitimate users access to a service. These attacks exploit the weakness within the TCP protocol where there is some state information for the connection the server needs to maintain. This often involves the use of TCP SYN messages.
CAPEC-486: UDP Flood
An adversary may execute a flooding attack using the UDP protocol with the intent to deny legitimate users access to a service by consuming the available network bandwidth. Additionally, firewalls often open a port for each UDP connection destined for a service with an open UDP port, meaning the firewalls in essence save the connection state thus the high packet nature of a UDP flood can also overwhelm resources allocated to the firewall. UDP attacks can also target services like DNS or VoIP which utilize these protocols. Additionally, due to the session-less nature of the UDP protocol, the source of a packet is easily spoofed making it difficult to find the source of the attack.
CAPEC-487: ICMP Flood
An adversary may execute a flooding attack using the ICMP protocol with the intent to deny legitimate users access to a service by consuming the available network bandwidth. A typical attack involves a victim server receiving ICMP packets at a high rate from a wide range of source addresses. Additionally, due to the session-less nature of the ICMP protocol, the source of a packet is easily spoofed making it difficult to find the source of the attack.
CAPEC-488: HTTP Flood
An adversary may execute a flooding attack using the HTTP protocol with the intent to deny legitimate users access to a service by consuming resources at the application layer such as web services and their infrastructure. These attacks use legitimate session-based HTTP GET requests designed to consume large amounts of a server's resources. Since these are legitimate sessions this attack is very difficult to detect.
CAPEC-489: SSL Flood
An adversary may execute a flooding attack using the SSL protocol with the intent to deny legitimate users access to a service by consuming all the available resources on the server side. These attacks take advantage of the asymmetric relationship between the processing power used by the client and the processing power used by the server to create a secure connection. In this manner the attacker can make a large number of HTTPS requests on a low provisioned machine to tie up a disproportionately large number of resources on the server. The clients then continue to keep renegotiating the SSL connection. When multiplied by a large number of attacking machines, this attack can result in a crash or loss of service to legitimate users.
CAPEC-490: Amplification
An adversary may execute an amplification where the size of a response is far greater than that of the request that generates it. The goal of this attack is to use a relatively few resources to create a large amount of traffic against a target server. To execute this attack, an adversary send a request to a 3rd party service, spoofing the source address to be that of the target server. The larger response that is generated by the 3rd party service is then sent to the target server. By sending a large number of initial requests, the adversary can generate a tremendous amount of traffic directed at the target. The greater the discrepancy in size between the initial request and the final payload delivered to the target increased the effectiveness of this attack.
CAPEC-491: Quadratic Data Expansion
An adversary exploits macro-like substitution to cause a denial of service situation due to excessive memory being allocated to fully expand the data. The result of this denial of service could cause the application to freeze or crash. This involves defining a very large entity and using it multiple times in a single entity substitution. CAPEC-197 is a similar attack pattern, but it is easier to discover and defend against. This attack pattern does not perform multi-level substitution and therefore does not obviously appear to consume extensive resources.
CAPEC-493: SOAP Array Blowup
An adversary may execute an attack on a web service that uses SOAP messages in communication. By sending a very large SOAP array declaration to the web service, the attacker forces the web service to allocate space for the array elements before they are parsed by the XML parser. The attacker message is typically small in size containing a large array declaration of say 1,000,000 elements and a couple of array elements. This attack targets exhaustion of the memory resources of the web service.
CAPEC-494: TCP Fragmentation
An adversary may execute a TCP Fragmentation attack against a target with the intention of avoiding filtering rules of network controls, by attempting to fragment the TCP packet such that the headers flag field is pushed into the second fragment which typically is not filtered.
CAPEC-495: UDP Fragmentation
An attacker may execute a UDP Fragmentation attack against a target server in an attempt to consume resources such as bandwidth and CPU. IP fragmentation occurs when an IP datagram is larger than the MTU of the route the datagram has to traverse. Typically the attacker will use large UDP packets over 1500 bytes of data which forces fragmentation as ethernet MTU is 1500 bytes. This attack is a variation on a typical UDP flood but it enables more network bandwidth to be consumed with fewer packets. Additionally it has the potential to consume server CPU resources and fill memory buffers associated with the processing and reassembling of fragmented packets.
CAPEC-496: ICMP Fragmentation
An attacker may execute a ICMP Fragmentation attack against a target with the intention of consuming resources or causing a crash. The attacker crafts a large number of identical fragmented IP packets containing a portion of a fragmented ICMP message. The attacker these sends these messages to a target host which causes the host to become non-responsive. Another vector may be sending a fragmented ICMP message to a target host with incorrect sizes in the header which causes the host to hang.
CAPEC-528: XML Flood
An adversary may execute a flooding attack using XML messages with the intent to deny legitimate users access to a web service. These attacks are accomplished by sending a large number of XML based requests and letting the service attempt to parse each one. In many cases this type of an attack will result in a XML Denial of Service (XDoS) due to an application becoming unstable, freezing, or crashing.