CVE-2024-10141
Jsbroks Coco Annotator 0.11.1
Raw vector
CVSS:4.0/AV:N/AC:H/AT:N/PR:N/UI:N/VC:L/VI:N/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2024-10141 is a medium-severity Predictable from Observable State (CWE-341) vulnerability in Jsbroks Coco Annotator. Its CVSS base score is 6.3 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Data Obfuscation (T1001); ranked in the top 44% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as Computer Vision; in the Other ATLAS/OWASP Terms risk domain.
The strongest mitigations our analysis identified map to IA-5 (Authenticator Management) and SC-12 (Cryptographic Key Establishment and Management) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-32933
Vulnerability Data
A vulnerability, which was classified as problematic, was found in jsbroks COCO Annotator 0.11.1. This affects an unknown part of the component Session Handler. The manipulation of the argument SECRET_KEY leads to predictable from observable state. It is possible to…
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initiate the attack remotely. The complexity of an attack is rather high. The exploitability is told to be difficult. The exploit has been disclosed to the public and may be used.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Computer Vision
- Risk Domain
- Other ATLAS/OWASP Terms
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- COCO Annotator is a web-based tool for annotating images in COCO format, primarily used for preparing datasets in computer vision tasks such as object detection in AI/ML workflows.
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V6.6.1V6.5.3V6.5.8
Mitigating Controls (NIST 800-53 r5) AI
Authenticator management requires generation and distribution of values that cannot be derived from observable state.
Cryptographic key establishment mandates use of unpredictable, non-observable values for keys and nonces.
Session authenticity protection requires session identifiers or tokens that resist prediction from network or timing observations.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Hardened configuration baselines can enforce use of cryptographically secure RNG sources and disable predictable state-based mechanisms.
Secure SDLC practices directly require cryptographically secure random values instead of observable state such as time or PID.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Cryptographic controls replace predictable values with high-entropy, non-guessable material.
SDLC requirements encourage secure design but do not directly mandate removal of predictable state.
Secure coding practices explicitly forbid use of predictable state (time, PID, counters) for secrets or tokens.
Security testing can detect predictability issues but does not prevent them by itself.