AI security incident: VU#924114: dr_flac contains an integer overflow vulnerability that allows for DoS whe...
Overview dr_flac , an open-source FLAC audio decoder, part of the dr_libs audio decoder toolset, contains an integer overflow vulnerability allowing for denial of service (DoS) when provided a specific crafted file. An attacker can exploit this vulnerability through providing a tool that uses dr_flac a specially crafted file, and can cause the tool to crash. The vulnerability, tracked as CVE-2025-14369, has been patched in commit b2197b2 of dr_flac. In an enterprise situation, audio tools that use dr_flac may be susceptible to crashes or other abnormal behavior if they process attacker-controlled files. Description dr_libs is an open-source audio decoding tool.
Why This Is AI-Related
This advisory is part of the public incident archive, but the current source material uses limited explicit AI terminology, so the cited sources should be reviewed carefully when judging AI relevance and exposure.
- Explicit AI-specific signals are limited in the current source material, so use the cited advisory to validate scope during triage.
Affected Workflow
Check inference endpoints, parsing layers, queues, and file processing jobs that support AI features.
Likely Attack Path
An attacker can drive resource exhaustion or crash conditions in the vulnerable component through crafted traffic or content.
Impact
The advisory describes an availability or resource-exhaustion path that can disrupt AI-serving components and supporting automation. Severity HIGH. Classification confidence 66%. Source channel RSS.
Detection And Triage Signals
- Latency spikes or worker restarts on AI-serving endpoints
- Memory or CPU saturation after malformed requests or artifacts
- Queue backlogs, timeouts, or repeated crash loops in model services
Recommended Response
- Identify inference endpoints, parsing jobs, or queues that rely on the affected component.
- Apply vendor mitigations and add rate, size, or input controls to reduce exhaustion risk during triage.
- Monitor latency, restart frequency, queue backlog, and saturation indicators for active disruption.
Compliance And Business Impact
Availability failures can interrupt customer-facing AI features and force emergency rollback or capacity isolation.
Sources
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