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CVE-2025-55136VulnerabilityPublished

CVE-2025-55136: tae898 ERC · Deserialization of Untrusted Data

Affects tae898 ERCSource CVE Database V5

0

Not known to be exploited · CVSS 5.7 Medium.

Data as of 25 Oct 2026, 19:02 UTC

CVSS 3.1 base score
5.7Medium
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.1% chance of exploitation in 30 days – higher than 4% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:C/C:L/I:L/A:N

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 7 Aug 2025

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponised: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq Mirage: no evidence on record.

    No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 2026-10-25.

What to do

Affected software

ProductAffectedFixed in
tae898 ERCAffected
  • =0
Fixed in–

AI-suggested

To mitigate CVE-2025-55136, European organizations should take several specific actions beyond generic advice: 1) Immediately assess whether ERC (Emotion Recognition in Conversation) software version 0.3 or earlier is deployed within their environment. 2) If deployed, isolate the application from critical network segments to limit potential impact. 3) Replace or upgrade the use of jsonpickle for deserialization with safer alternatives that do not allow arbitrary code execution, such as using strict JSON parsers or implementing allowlists for deserialized classes. 4) Implement strict input validation and sanitization on all data inputs that are deserialized by the application. 5) Monitor application logs and network traffic for unusual deserialization activities or unexpected object types. 6) Apply application-layer firewalls or runtime application self-protection (RASP) solutions that can detect and block malicious deserialization attempts. 7) Engage with the ERC software maintainers or community to obtain patches or updates addressing this vulnerability as they become available. 8) Conduct security code reviews and penetration testing focused on deserialization processes within ERC or similar applications. 9) Educate developers and security teams about the risks of insecure deserialization and secure coding practices to prevent recurrence.

Description

ERC (aka Emotion Recognition in Conversation) through 0.3 has insecure deserialization via a serialized object because jsonpickle is used.

References

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