Cyber Resilience

CVE-2025-28357

Published
01 October 2025
Modified
05 July 2026
CVSS Score v3.1 8.8
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
EPSS Score 0.0041 34th percentile
Risk Priority 64 floored blend · peak EPSS

CVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.

Summary

CVE-2025-28357 is a high-severity CRLF Injection (CWE-93) vulnerability. Its CVSS base score is 8.8 (High).

Operationally, exploitation aligns with the MITRE ATT&CK technique Content Injection (T1659); ranked at the 34th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.

The strongest mitigations our analysis identified map to SI-10 (Information Input Validation) — 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-2025-28357, published on 2025-10-01, is a CRLF injection vulnerability (CWE-93) in Neto CMS versions v6.313.0 through v6.314.0. The flaw allows attackers to execute arbitrary code by supplying a crafted HTTP request. It carries a CVSS v3.1 base score of 8.8 (AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H), indicating high severity due to its potential for remote exploitation with significant impacts.

Unauthenticated attackers can exploit this vulnerability over the network with low attack complexity, though it requires user interaction, such as tricking a user into processing a malicious request. Successful exploitation enables arbitrary code execution, compromising confidentiality, integrity, and availability on the affected Neto CMS instance.

Mitigation details and further advisories are available from the vendor at http://neto.com and in the report at https://github.com/ShadowByte1/CVE-Reports/blob/main/CVE-2025-28357.md.

OWASP Top 10 for Web (2025)

EU & UK References

Vulnerability Data

A CRLF injection vulnerability in Neto CMS v6.313.0 through v6.314.0 allows attackers to execute arbitrary code via supplying a crafted HTTP request.

CWE(s)

Related Threats

MITRE ATT&CK Enterprise Techniques

T1659 Content Injection Initial Access
Adversaries may gain access and continuously communicate with victims by injecting malicious content into systems through online network traffic.
T1190 Exploit Public-Facing Application Initial Access
Adversaries may attempt to exploit a weakness in an Internet-facing host or system to initially access a network.
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2026-43968Shared CWE-93
CVE-2026-34458Shared CWE-93
CVE-2026-12357Shared CWE-93
CVE-2026-20113Shared CWE-93
CVE-2026-39394Shared CWE-93
CVE-2026-44217Shared CWE-93
CVE-2026-77634Shared CWE-93
CVE-2026-6351Shared CWE-93
CVE-2026-45070Shared CWE-93
CVE-2026-35504Shared CWE-93

Affected Assets

Mitigating Controls

Control response

Prevent
Stop it (NIST 800-53)

—

Detect
Catch it (NIST detect / respond)

—

Harden
Shrink the surface (DISA STIG)

—

Validate
Prove the fix (OWASP ASVS)
  • V4.2.4

Mitigating Controls (NIST 800-53 r5) AI

Input validation directly stops untrusted data containing CRLF sequences from reaching the component that treats CRLF as a delimiter.

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 require input neutralization and validation to block CRLF injection.

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.

finds

Security testing can detect CRLF flaws but does not itself implement the neutralization.

prevents

Secure development lifecycle mandates input validation and output encoding that directly prevents CRLF injection.

prevents

Application security requirements include rules for neutralizing special characters such as CRLF in inputs.

prevents

Secure architecture principles encourage safe handling of untrusted data but do not prescribe specific CRLF controls.

prevents

Secure coding standards explicitly require neutralization of CRLF sequences, fully addressing this weakness.

References