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CVE-2026-85696 – Unauthenticated Remote Code Execution – SadTalker ≤ 0.0.2

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Summary

CVE-2026-85696 is an OS command injection vulnerability in OpenTalker’s SadTalker, an open-source AI tool that generates talking-face animation videos from a still image and an audio clip. The flaw lies in the video muxing process, where uploaded audio filenames are passed into ffmpeg shell commands without proper sanitization, allowing an unauthenticated remote attacker to execute arbitrary operating system commands. The vulnerability is rated critical severity.

Technical details

  • Root cause: SadTalker builds ffmpeg command-line invocations by directly interpolating the uploaded audio file’s filename into the command string, without escaping shell metacharacters (in src/utils/videoio.py).
  • Trigger condition: An attacker uploads an audio file whose filename contains shell metacharacters, then triggers the normal video-generation workflow.
  • Attack vector: Network-based; no authentication and no user interaction beyond the attacker’s own upload/generation request are required.
  • Impact: Arbitrary OS command execution on the server hosting SadTalker, potentially leading to full compromise of confidentiality, integrity, and availability of the host.

Affected software

  • OpenTalker SadTalker, versions 0 through 0.0.2 (all releases up to and including 0.0.2)

Severity

  • CVSS v3.1 Base Score: 9.8 (Critical) — CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
  • CVSS v4.0 Base Score: 9.3 (Critical) — CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N

Mitigation and recommended actions

  • Immediate: No official patched release has been published by the OpenTalker maintainers as of this writing; the tracking issue remains open. Monitor the upstream repository for a fixed release and upgrade as soon as one is available.
  • If no patch is available:
    • Do not expose SadTalker instances that accept audio uploads directly to the internet; restrict access to trusted internal networks or place behind authenticated access controls.
    • Sanitize or reject uploaded filenames containing shell metacharacters at a reverse proxy or application layer before they reach the SadTalker processing pipeline.
    • Run the SadTalker service with least-privilege, sandboxed/containerized execution to limit the blast radius of command execution.
    • Monitor logs for unexpected ffmpeg invocations or anomalous filenames in upload requests.

How IONIX identifies potentially affected assets

IONIX matches the following signals against data already collected when it crawled the asset; identifying the technology sends no request beyond that crawl.

  • Raw response body: SadTalker...Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation, <gradio-app

References

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How IONIX’s External Exposure Management Platform Detects and Validates
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1

Map your entire attack surface (continously)

IONIX uses multi-factor discovery methods, including DNS analysis, certificate mapping, metadata inspection, and more, to automatically map every internet-facing asset across your environment. This includes cloud instances, third-party platforms, shadow IT, and even forgotten infrastructure that traditional tools miss.

2

Monitor for new CVEs

Dozens of threat intel feeds using agentic technology are continuously analyzed to detect the appearance of proof-of-concept code, exploit kits, and indicators of active targeting. IONIX goes further by applying AI to proactively evaluate whether emerging vulnerabilities are likely to be exploited, even before PoCs go public.

3

Identify Potential External Exposures

Not all CVEs matter. IONIX filters vulnerabilities by asking attacker-centric questions: Can it be reached from the internet? Does it require authentication? Is it being exploited in the wild? This dramatically reduces noise and focuses teams on threats that can actually be weaponized.

4

Create Safe, Scalable Exploit Validations

IONIX transforms real-world PoCs into safe, non-intrusive test payloads that can be run in production environments without disruption. These simulations are precisely targeted to the systems that are vulnerable, ensuring rapid validation without unnecessary load.

5

Execute Exploit Validations

By combining context about software stack, versioning, exposure status, and reachability, IONIX ensures that only the right payloads are executed against the right assets, maximizing efficiency and minimizing risk.

6

Drive Fast and Actionable Remediation

Results are routed through integrations with ticketing, SOAR, and SIEM tools. Issues are written in plain language, bundled into remediation clusters, and prioritized based on asset criticality, exploitability, and blast radius. This shortens mean time to remediation (MTTR) and empowers teams to act with confidence.

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