CVE-2025-56423: Sciences Austrian Archaeological Institute OpenAtlas · Observable Discrepancy
Source CVE Database V5
Not known to be exploited · CVSS 5.3 Medium.
Data as of 26 Oct 2026, 10:12 UTC
- EPSS
- 0.3% chance of exploitation in 30 days – higher than 26% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:NExploitation evidence
Disclosed: evidence found.
CVE published 24 Nov 2025
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by 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 26 Oct 2026.
What to do
AI-suggested
Organizations should immediately review and modify the OpenAtlas login error handling to avoid disclosing sensitive information. This includes standardizing error messages to generic responses that do not reveal whether a username exists or the nature of the authentication failure. Network-level controls such as rate limiting and IP blacklisting should be implemented to prevent automated enumeration attempts. Monitoring authentication logs for unusual patterns or repeated failed login attempts can help detect exploitation attempts early. In parallel, multi-factor authentication (MFA) should be enforced to reduce the risk of compromised credentials. Conducting security awareness training for users about phishing and credential security is also recommended. Finally, organizations should consider isolating OpenAtlas systems within segmented network zones to limit exposure.
Description
An issue in Austrian Academy of Sciences (AW) Austrian Archaeological Institute OpenAtlas v.8.12.0 allows a remote attacker to obtain sensitive information via the login error messages