CVE-2025-66909
Turms-Im Turms 0.10.0-snapshot
Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:HSummary
CVE-2025-66909 is a high-severity Data Amplification (CWE-409) vulnerability in Turms-Im Turms. Its CVSS base score is 7.5 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Endpoint Denial of Service (T1499); ranked at the 40th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as Deep Learning Frameworks; in the Data-Related Vulnerabilities risk domain.
The strongest mitigations our analysis identified map to SI-10 (Information Input Validation) and SC-5 (Denial-of-service Protection) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-204541
Vulnerability Data
Turms AI-Serving module v0.10.0-SNAPSHOT and earlier contains an image decompression bomb denial of service vulnerability. The ExtendedOpenCVImage class in ai/djl/opencv/ExtendedOpenCVImage.java loads images using OpenCV's imread() function without validating dimensions or pixel count before decompression. An attacker can upload a specially…
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crafted compressed image file (e.g., PNG) that is small when compressed but expands to gigabytes of memory when loaded. This causes immediate memory exhaustion, OutOfMemoryError, and service crash. No authentication is required if the OCR service is publicly accessible. Multiple requests can completely deny service availability.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Deep Learning Frameworks
- Risk Domain
- Data-Related Vulnerabilities
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: ai, opencv
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Input validation can reject or limit decompression of data whose expansion ratio exceeds safe thresholds.
DoS protection limits the resource-exhaustion impact when a decompression bomb is processed.
Resource allocation controls bound memory/CPU consumption that a data-amplification attack would otherwise exhaust.
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.
Secure-development practices include input-validation and resource-limit checks that prevent improper handling of compressed data.
Runtime monitoring of compute resources can detect exhaustion caused by decompression bombs.
Capacity planning and monitoring directly limits the availability impact of data-amplification attacks.
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.
Security testing can uncover decompression-bomb vulnerabilities before release.
Redundancy helps availability but does not address the root cause of the weakness.
Monitoring can detect anomalous resource usage but does not prevent the weakness.
Secure development lifecycle includes input validation and resource-limit checks that mitigate data-amplification attacks.
Application security requirements can mandate limits on decompression size and ratio.
Secure architecture principles encourage defensive design against resource-exhaustion threats.