CWE-345 Classe Brouillon

Insufficient Verification of Data Authenticity

This vulnerability occurs when an application fails to properly check where data comes from or confirm its legitimacy, allowing untrusted or forged information to be processed as valid.

Définition

What is CWE-345?

This vulnerability occurs when an application fails to properly check where data comes from or confirm its legitimacy, allowing untrusted or forged information to be processed as valid.
Insufficient verification of data authenticity is a common root cause for security flaws like spoofing, CSRF, and replay attacks. It happens when developers trust data based solely on its apparent format or origin, without enforcing strong cryptographic signatures, secure tokens, or proper chain-of-trust validation. Attackers exploit this by tampering with requests, forging headers, or replaying captured data to impersonate users, bypass authorization, or trigger unauthorized actions. To prevent this, always cryptographically verify the source and integrity of critical data—such as session tokens, API requests, and file uploads—using standards like digital signatures, anti-CSRF tokens, and secure challenge-response mechanisms. Managing these validation checks consistently across a complex application landscape is challenging. An ASPM platform like Plexicus can automatically detect missing authenticity checks across your codebase and runtime, using AI to generate precise remediation guidance, ensuring your verification logic is robust and uniformly applied.
Impact réel

Real-world CVEs caused by CWE-345

  • Distributed Control System (DCS) does not sign firmware images and only relies on insecure checksums for integrity checks

  • Distributed Control System (DCS) does not sign firmware images and only relies on insecure checksums for integrity checks

  • Remote Terminal Unit (RTU) does not use signatures for firmware images and relies on insecure checksums

Comment les attaquants l'exploitent

Parcours de l'attaquant étape par étape

  1. 1

    Identifier un chemin de code qui traite des entrées non fiables sans validation.

  2. 2

    Élaborer une charge utile qui exploite le comportement non sécurisé — injection, traversal, débordement ou abus de logique.

  3. 3

    Délivrer la charge utile via une requête normale et observer la réaction de l'application.

  4. 4

    Itérer jusqu'à ce que la réponse divulgue des données, exécute le code de l'attaquant ou élève les privilèges.

Exemple de code vulnérable

Vulnerable pseudo

MITRE n'a pas publié d'exemple de code pour ce CWE. Le motif ci-dessous est illustratif — voir Ressources pour les références canoniques.

Vulnérable pseudo
// Example pattern — see MITRE for the canonical references.
function handleRequest(input) {
  // Untrusted input flows directly into the sensitive sink.
  return executeUnsafe(input);
}
Exemple de code sécurisé

Secure pseudo

Sécurisé pseudo
// Validate, sanitize, or use a safe API before reaching the sink.
function handleRequest(input) {
  const safe = validateAndEscape(input);
  return executeWithGuards(safe);
}
What changed: the unsafe sink is replaced (or the input is validated/escaped) so the same payload no longer triggers the weakness.
Liste de contrôle de prévention

How to prevent CWE-345

  • Architecture Use safe-by-default frameworks and APIs that prevent the unsafe pattern from being expressible.
  • Implementation Validate input at trust boundaries; use allowlists, not denylists.
  • Implementation Apply the principle of least privilege to credentials, file paths, and runtime permissions.
  • Testing Cover this weakness in CI: SAST rules + targeted unit tests for the data flow.
  • Operation Monitor logs for the runtime signals listed in the next section.
Signaux de détection

How to detect CWE-345

Automated Static Analysis High

Automated static analysis, commonly referred to as Static Application Security Testing (SAST), can find some instances of this weakness by analyzing source code (or binary/compiled code) without having to execute it. Typically, this is done by building a model of data flow and control flow, then searching for potentially-vulnerable patterns that connect "sources" (origins of input) with "sinks" (destinations where the data interacts with external components, a lower layer such as the OS, etc.)

CWE-345

Don't catalog this weakness. Prove it's reachable.

Plexicus turns CWE catalogs into evidence: every CWE-pattern is matched against your real code graph, reach is proven on a sandbox clone, and verified findings ship as reviewed PRs.

Questions fréquentes

Frequently asked questions

Qu'est-ce que CWE-345 ?

This vulnerability occurs when an application fails to properly check where data comes from or confirm its legitimacy, allowing untrusted or forged information to be processed as valid.

Quelle est la gravité de CWE-345 ?

MITRE n'a pas publié de note de probabilité d'exploitation pour cette faiblesse. Traitez-la comme un impact moyen jusqu'à ce que votre modèle de menace prouve le contraire.

Quels langages ou plateformes sont affectés par CWE-345 ?

MITRE lists the following affected platforms: ICS/OT.

Comment puis-je prévenir CWE-345 ?

Use safe-by-default frameworks, validate untrusted input at trust boundaries, and apply the principle of least privilege. Cover the data-flow signature in CI with SAST.

Comment Plexicus détecte et corrige CWE-345 ?

Le moteur SAST de Plexicus reconnaît la signature de flux de données de CWE-345 à chaque commit. Lorsqu'une correspondance est trouvée, notre agent Codex Remedium ouvre une PR de correction avec le code corrigé, les tests et un résumé d'une ligne pour le relecteur.

Où puis-je en savoir plus sur CWE-345 ?

MITRE publie la définition canonique à https://cwe.mitre.org/data/definitions/345.html. Vous pouvez également consulter la documentation OWASP et NIST pour des conseils adjacents.

Faiblesses associées

Weaknesses related to CWE-345

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CWE-1291 Frère

Public Key Re-Use for Signing both Debug and Production Code

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CWE-1318 Frère

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SAMPLE HANDOVER · ILLUSTRATIVE

Sample evidence handover

A trimmed view of what your team receives at the end of an AI Swarm Pentest engagement. Real engagements include full technical evidence, executive narrative, and a remediation plan.

VALIDATED FINDING Evidence attached

Server-Side Request Forgery in webhooks/receiver

demo-project/sample-app · src/webhooks/receiver.py:42

SeverityHigh CVSS 3.18.6 Priority79 Confirmedvia replay

Untrusted caller-supplied URLs reach an internal egress without an allowlist. Replayed in a sandbox against a fresh authorized target — the same control was validated to fail twice.

REVIEWER-READY REMEDIATION Merge-ready PR

Validate the target URL against an allowlist of permitted hostnames. Reject private/internal IP ranges. Enforce HTTPS only.

plexicus/remediation/webhooks-ssrf 3 changed · 0 new files
42resp = requests.get(target_url)
42+if not is_allowed_host(target_url):
43+  raise WebhookRejected(target_url)
44+resp = requests.get(target_url, timeout=5)
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  • Validated findings list
  • Merge-ready PRs
  • Compliance mapping (NIS2 · DORA · CRA)
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