Cyber Resilience

CVE-2025-26013

Info Disclosure in Olajowon Loggrove 1.0

Public PoCInfo Disclosure
Published
21 February 2025
Modified
13 June 2025
Patch / advisory
CVSS Score v3.1 8.2
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:L/A:N
EPSS Score 0.0040 33th percentile
Risk Priority 62 floored blend · peak EPSS

Summary

CVE-2025-26013 is a high-severity Inclusion of Sensitive Information in Source Code (CWE-540) vulnerability in Olajowon Loggrove. Its CVSS base score is 8.2 (High).

Operationally, exploitation aligns with the MITRE ATT&CK technique Code Repositories (T1213.003); ranked at the 33th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.

The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and AC-3 (Access Enforcement) — see the control section below for these in your framework.

Deeper analysis AI-assisted summary

Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.

CVE-2025-26013 is an information disclosure vulnerability in Loggrove version 1.0, specifically within the read.py component. Published on 2025-02-21, the issue enables a remote attacker to obtain sensitive information. It carries a CVSS v3.1 base score of 8.2 (AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:L/A:N) and is classified under CWE-540.

The vulnerability can be exploited by any remote attacker over the network, requiring low attack complexity, no privileges, and no user interaction. Successful exploitation grants high-impact access to sensitive information, with a low integrity impact but no effect on availability.

Mitigation details are available in the referenced advisory at https://gitee.com/olajowon/loggrove/issues/IBJSXS.

OWASP Top 10 for Web (2025)

EU & UK References

Vulnerability Data

An issue in Loggrove v.1.0 allows a remote attacker to obtain sensitive information via the read.py component.

CWE(s)

Related Threats

MITRE ATT&CK Enterprise Techniques

T1213.003 Code Repositories Collection
Adversaries may leverage code repositories to collect valuable information.
T1552.001 Credentials In Files Credential Access
Adversaries may search local file systems and remote file shares for files containing insecurely stored credentials.
T1213 Data from Information Repositories Collection
Adversaries may leverage information repositories to mine valuable information.
T1552 Unsecured Credentials Credential Access
Adversaries may search compromised systems to find and obtain insecurely stored credentials.
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2025-26014Same product: Olajowon Loggrove
CVE-2025-26047Same product: Olajowon Loggrove
CVE-2024-39729Shared CWE-540
CVE-2024-2265Shared CWE-540
CVE-2024-27257Shared CWE-540
CVE-2026-22275Shared CWE-540
CVE-2024-1272Shared CWE-540
CVE-2024-9596Shared CWE-540
CVE-2024-8417Shared CWE-540
CVE-2025-0923Shared CWE-540

Affected Assets

olajowon
loggrove
1.0

Mitigating Controls

Mitigating Controls (NIST 800-53 r5) AI

Developer testing and static analysis locate hard-coded sensitive values before code is deployed.

Enforces access so that source containing embedded secrets cannot be reached by unauthorized parties.

Engineering principles require secrets to be externalized rather than embedded in source.

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.

PR.PS-06 mostly match
prevents

Secure SDLC practices directly prohibit embedding secrets or sensitive data in source code.

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.

degrades

Directly restricts access to source code, preventing exposure of embedded sensitive information.

prevents

Secure coding standards explicitly prohibit hard-coding credentials or sensitive data.

prevents

Classification helps identify source code containing sensitive data so it can be protected.

prevents

Access control limits who can view or retrieve source code that may contain secrets.

prevents

Secure SDLC practices include removing secrets from code before commit or deployment.

mitigates

Environment separation reduces risk of accidental exposure but does not address secrets already in code.

References