CVE-2023-1177 (GCVE-0-2023-1177)
Vulnerability from cvelistv5 – Published: 2023-03-24 00:00 – Updated: 2025-02-19 20:56Title
Path Traversal: '\..\filename' in mlflow/mlflow
Summary
Path Traversal: '\..\filename' in GitHub repository mlflow/mlflow prior to 2.2.1.
Severity
9.3 (Critical)
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-02-19 20:56 UTC
CWE
- CWE-29 - Path Traversal: '\..\filename'
Assigner
References
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| mlflow | mlflow/mlflow |
Affected:
unspecified , < 2.2.1
(custom)
|
guessed |
Shadowserver
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: 8291f022-16cd-41a2-a207-d4dd6e982a44
Exploited: Yes
Characteristics
Severity:
98.0
Timestamps
First Seen: 2023-10-14
Asserted: 2023-10-14
Last Seen: 2026-09-06
Scope
Asset Exposure: ['internet-facing']
Notes: Affected: MLflow / MLflow | Class: other-software | Severity: Critical (CVSS 9.8) | IoT: no | In CISA KEV: no | Honeypot connections on 2026-09-06: 75
Evidence
Type: Honeypot
Signal: In The Wild Attempts
Confidence: 70%
Source: shadowserver
Details
| 1D | 3 |
|---|---|
| Iot | no |
| Feed | Shadowserver Foundation honeypot/exploited-vulnerabilities |
| Type | http-scan |
| Class | other-software |
| 7D Avg | 2 |
| Vendor | MLflow |
| 30D Avg | 1 |
| 90D Avg | 4 |
| Product | MLflow |
| Cisa Kev | no |
| Connections | 75 |
| Observation Date | 2026-09-06 |
| Vulnerability Class | CVSS |
| Vulnerability Score | 9.8 |
| Vulnerability Severity | Critical |
References
Created: 2026-07-01 05:54 UTC
| Updated: 2026-09-08 01:00 UTC
Previdian
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: 00c0b32c-3588-4bae-bccb-59b142d4f3c1
Exploited: Yes
Timestamps
First Seen: 2025-07-07
Asserted: 2025-07-07
Scope
Notes: KEVIntel entry: Path Traversal: '\..\filename' in mlflow/mlflow | Affected: mlflow / mlflow/mlflow | CVSS: 9.3 (CRITICAL) | Used in malware: unknown | Not yet in CISA KEV: True
Evidence
Type: Public Report
Signal: Successful Exploitation
Confidence: 70%
Source: kevintel
Details
| Feed | KEVIntel (kevintel.com) |
|---|---|
| Title | Path Traversal: '\..\filename' in mlflow/mlflow |
| Vendor | mlflow |
| Product | mlflow/mlflow |
| Added Date | 2025-07-07T00:00:00.000Z |
| Cvss Score | 9.3 |
| Epss Score | None |
| Cvss Severity | CRITICAL |
| Epss Percentile | None |
| Used In Malware | unknown |
| Ahead Of Cisa Kev | None |
| Not Yet In Cisa Kev | True |
References
Created: 2026-06-23 11:12 UTC
| Updated: 2026-06-23 11:12 UTC
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
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.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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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.
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