CVE-2026-66372 in VA1G4 Recorder
Summary
by MITRE • 09/16/2026
The affected products use insufficiently random values, which allows web session tokens to be predictable, bounding token entropy to the seed space.
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Analysis
by VulDB Data Team • 09/16/2026
The vulnerability described constitutes a critical failure in cryptographic randomness generation, specifically affecting the mechanism used for creating web session identifiers. In secure application architecture, session tokens serve as the primary credential that authenticates a user's identity during an active browsing session. When these tokens are generated using insufficiently random values, they become susceptible to prediction attacks. This flaw implies that the underlying pseudo-random number generator (PRNG) or algorithm lacks sufficient entropy sources, resulting in output sequences that exhibit patterns or biases rather than true statistical randomness. Consequently, the effective security of the token is not determined by its bit length but is instead bounded by the size and unpredictability of the seed space used to initialize the randomization process. If an attacker can determine or guess this seed value, they can reproduce the sequence of tokens generated for any user within that system's operational window.
From a technical perspective, this issue aligns directly with CWE-330: Use of Insufficiently Random Values and CWE-614: Sensitive Cookie in Session ID Without Secure Flag if combined with transmission flaws, though the core defect is rooted in randomness quality. The predictability arises because many programming languages or frameworks rely on default PRNG implementations that may be seeded with low-entropy data such as process IDs, timestamps, or static constants. An attacker observing a few valid session tokens can perform statistical analysis to reverse-engineer the internal state of the generator. Once the state is known, future and potentially past tokens can be calculated with high probability. This transforms what should be an opaque authentication mechanism into a transparent one, allowing unauthorized entities to hijack active sessions without needing to crack complex passwords or exploit other application logic errors.
The operational impact of this vulnerability is severe, leading primarily to session hijacking and privilege escalation. An attacker who successfully predicts valid session tokens can impersonate legitimate users by injecting the predicted token into their own browser cookies or HTTP headers. This grants them full access to the victim's account, including sensitive personal data, financial information, and administrative capabilities if the compromised account holds elevated privileges. In multi-tenant environments or systems handling critical infrastructure, this breach of identity integrity can lead to widespread data exfiltration, regulatory non-compliance with standards such as GDPR or HIPAA, and significant reputational damage. Furthermore, because session tokens are often used for state-changing operations like password resets or fund transfers, the attacker gains the ability to perform actions on behalf of the victim, effectively bypassing authentication controls entirely.
Mitigation strategies must focus on strengthening the entropy sources and ensuring the use of cryptographically secure random number generators. Developers should replace standard PRNGs with CSPRNGs such as /dev/urandom on Unix-like systems or CryptGenRandom on Windows platforms, which are designed to resist prediction even if part of their internal state is exposed. It is crucial that these generators are seeded with high-entropy data from multiple sources, including hardware-based noise generators where available, rather than relying solely on system time or process identifiers. Additionally, session tokens should be sufficiently long, typically at least 128 bits, to ensure brute-force resistance even if the generator has minor weaknesses. Implementing secure cookie attributes such as HttpOnly and Secure can mitigate some risks associated with token theft via cross-site scripting but do not address the fundamental flaw of predictability. Regular security audits focusing on authentication flows and randomization implementations are essential to detect and remediate these subtle cryptographic failures before they can be exploited in production environments.