Cyber Resilience

CVE-2024-10141

Jsbroks Coco Annotator 0.11.1

Public PoC
Published
19 October 2024
Modified
23 October 2024
CVSS Score v4 6.3
Click a component to see what it means
Raw vectorCVSS: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:X
EPSS Score 0.0081 54th percentile
Risk Priority 33 floored blend · peak EPSS

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 Browser Session Hijacking (T1185); ranked in the top 46% 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

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…

more

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)
CWE-341NVD-CWE-Other

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

T1185 Browser Session Hijacking Collection
Adversaries may take advantage of security vulnerabilities and inherent functionality in browser software to change content, modify user-behaviors, and intercept information as part of various browser session hijacking techniques.
attack.mitre.org →
T1563 Remote Service Session Hijacking Lateral Movement
Adversaries may take control of preexisting sessions with remote services to move laterally in an environment.
attack.mitre.org →
T1606 Forge Web Credentials Credential Access
Adversaries may forge credential materials that can be used to gain access to web applications or Internet services.
attack.mitre.org →
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2026-2108Same product: Jsbroks Coco Annotator
CVE-2026-2109Same product: Jsbroks Coco Annotator
CVE-2026-42365Shared CWE-341
CVE-2026-38968Shared CWE-341
CVE-2025-40780Shared CWE-341
CVE-2025-48461Shared CWE-341
CVE-2025-42925Shared CWE-341
CVE-2026-36609Shared CWE-341
CVE-2023-49259Shared CWE-341
CVE-2026-5081Shared CWE-341

Affected Assets

jsbroks
coco annotator
0.11.1

Mitigating Controls

Control response

Prevent
Stop it (NIST 800-53)

—

Detect
Catch it (NIST detect / respond)

—

Harden
Shrink the surface (DISA STIG)

—

Validate
Prove the fix (OWASP ASVS)
  • V6.6.1
  • V6.5.1
  • V6.5.3
  • V6.5.5

Mitigating Controls (NIST 800-53 r5) AI

IA-5 Authenticator Management good match

Authenticator management requires generation and distribution of values that cannot be derived from observable state.

SC-12 Cryptographic Key Establishment and Management good match

Cryptographic key establishment mandates use of unpredictable, non-observable values for keys and nonces.

SC-23 Session Authenticity good match

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.

PR.PS-06 mostly match
prevents

Secure SDLC practices directly require cryptographically secure random values instead of observable state such as time or PID.

PR.PS-01 partial match
prevents

Hardened configuration baselines can enforce use of cryptographically secure RNG sources and disable predictable state-based mechanisms.

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.

A.8.24 Use of cryptography mostly match
prevents

Cryptographic controls replace predictable values with high-entropy, non-guessable material.

A.8.29 Security testing in development and acceptance mostly match
finds

Security testing can detect predictability issues but does not prevent them by itself.

A.8.25 Secure development life cycle partial match
prevents

SDLC requirements encourage secure design but do not directly mandate removal of predictable state.

A.8.28 Secure coding partial match
prevents

Secure coding practices explicitly forbid use of predictable state (time, PID, counters) for secrets or tokens.

A.8.5 Secure authentication partial match
prevents

Strong authentication mechanisms reduce reliance on predictable state-derived tokens or identifiers.

A.8.17 Clock synchronization none match
none

Accurate time sources limit one observable state vector but do not address broader predictability.

References