Attack ChainAIDerived
Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain
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ReconAccess public LoLLMs endpoint
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DeliveryRegister low-privilege account or intercept JWT
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ExploitOffline brute-force JWT secret using hashcat
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InstallForge admin JWT payload
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C2Resign token with recovered secret
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ExecuteReplay forged token to admin endpoints
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ImpactExecute privileged operations
Vulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A01:2025 - Broken Access Control
ASVS 5.0
V8 - Authorization Access control enforcement
MITRE ATT&CK
1 technique across 1 tactic: Defense Evasion The technique list with ATT&CK links and the kill-chain view is part of the Basic plan and up. |
| Exploitation Conditions | Remote unauthenticated exploitation against default configurations of LoLLMs 2.1.0. The only prerequisite is network reachability to the LoLLMs web interface or API endpoints-no authentication, special privileges, or user interaction required per CVSS vector AV:N/AC:L/PR:N/UI:N. The weak JWT secret appears to be a default or hardcoded value in version 2.1.0, meaning all unpatched instances share the same vulnerability without requiring any non-default configuration. Exploitation is a two-phase attack: phase one (offline brute-force) requires obtaining any valid JWT token, which can be trivially acquired by creating a free user account if registration is enabled, or intercepting network traffic if the application lacks HTTPS enforcement. Phase two (token forgery and replay) requires only the recovered secret and basic JWT manipulation tools. Limiting factors: exploitation requires technical knowledge of JWT internals and access to brute-force tooling (hashcat, John the Ripper), which slightly raises the skill floor beyond script-kiddie level. The offline attack phase leaves no logs on the target system, making detection impossible until forged tokens are used. Deployments behind VPNs, IP allowlists, or with user registration disabled reduce initial token acquisition opportunities but do not prevent exploitation by authenticated low-privilege users or network-adjacent attackers. |
| Impact | CVSS 9.8 (Critical) reflects network attack vector, low complexity, no privileges or user interaction required, and high impact across confidentiality, integrity, and availability-textbook authentication bypass scenario. However, real-world risk factors present a mixed picture. EPSS score of 0.04% (14th percentile) indicates very low observed exploitation probability in the wild, suggesting this vulnerability affects a niche product with limited attacker interest or that exploitation requires specialized knowledge of the LoLLMs deployment environment. SSVC assessment confirms proof-of-concept availability and classifies the attack as automatable with total technical impact, which would normally elevate priority, but the exploitation=poc status (not 'active') and low EPSS suggest targeted rather than opportunistic threats. No CISA KEV listing confirms this is not being exploited at scale. Primary risk is to organizations using LoLLMs 2.1.0 in production environments where administrative access provides lateral movement or data exfiltration opportunities. The offline nature of the attack means defenders cannot detect brute-forcing in logs, making this a silent privilege escalation vector once an attacker obtains any valid JWT (even a low-privilege one) to use as a template. Patch availability in 2.2.0 significantly reduces risk for actively maintained deployments, but unmaintained or containerized instances may remain vulnerable indefinitely. |
| Exploit ScenarioDerived | An attacker with network access to a LoLLMs 2.1.0 instance first captures any JWT token by registering a low-privilege account or intercepting traffic. Using the captured token as a template, the attacker extracts the HMAC signature and header/payload, then launches an offline brute-force attack using hashcat with common password dictionaries and weak key patterns against the JWT signature. Within hours (depending on secret complexity), the attacker recovers the signing secret. They then modify the JWT payload to set administrative flags (e.g., 'role':'admin', 'isAdmin':true), resign the token using the cracked secret and HS256 algorithm, and replay the forged token in API requests to restricted administrative endpoints. The application validates the signature successfully and grants full administrative access, allowing the attacker to extract sensitive data, modify system configurations, create backdoor accounts, or deploy malicious payloads through LoLLMs model management features. Proof-of-concept code demonstrating JWT cracking and forgery is publicly available per SSVC exploitation status. |
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Alert meAnalysisAIv2 – Apr 28, 2026
Weak JWT secret key in LoLLMs 2.1.0 enables offline brute-force recovery, allowing remote unauthenticated attackers to forge administrative tokens and bypass authentication completely. Attackers can escalate privileges to administrator, impersonate legitimate users, and access all restricted endpoints without prior authentication. EPSS probability is low (0.04%, 14th percentile) suggesting limited widespread exploitation interest, though a proof-of-concept exists and SSVC classifies the vulnerability as automatable with total technical impact. Fixed in version 2.2.0 via commit a3b2b82b84.
Earlier versions of this analysis (1)
JWT secret key brute-forcing in Parisneo Lollms 2.1.0 allows unauthenticated remote attackers to forge administrative tokens and achieve full system compromise. The application uses a weak secret for signing JSON Web Tokens, enabling offline attacks to recover credentials and escalate privileges to administrator level. With CVSS 9.8 (critical network-accessible attack requiring no privileges) and EPSS data unavailable, this represents a severe authentication bypass in AI/LLM management software. Fixed in version 2.2.0. No public exploit identified at time of analysis, though the attack technique (JWT cracking) is well-documented.
RemediationAI
Upgrade immediately to LoLLMs version 2.2.0 or later, which resolves the weak JWT secret issue per commit a3b2b82b84d537a9da63e63a370a6a8ad55fed34 available at https://github.com/parisneo/lollms/commit/a3b2b82b84d537a9da63e63a370a6a8ad55fed34. The patch replaces the weak secret with a cryptographically secure randomly generated key. For environments where immediate upgrade is not feasible, implement the following compensating controls with noted limitations: (1) Manually regenerate the JWT secret in configuration files using a cryptographically secure random generator (32+ bytes, base64 encoded) and restart the application-this invalidates all existing tokens and requires user re-authentication but does not address the underlying weak default, so validate the new secret meets NIST SP 800-132 guidelines for key derivation; (2) Deploy network segmentation to restrict LoLLMs administrative endpoints to trusted IP ranges only via firewall rules or reverse proxy ACLs-reduces attack surface but does not prevent exploitation by insider threats or compromised trusted networks; (3) Implement additional authentication layers such as mutual TLS or API gateway tokens in front of LoLLMs-adds defense in depth but introduces latency and operational complexity. Note that rotating secrets alone is insufficient if the application redeploys with the same weak default on next restart. Advisory available at https://huntr.com/bounties/608b2a3b-2225-438e-9e61-ffbfdec2ed89.
Affected VersionsENISA
Affected Packages
Source: OSV (Open Source Vulnerabilities)
Affects your stack
Affects 2 packages in pypi, euvd
Checking this CVE against your own stacks and servers is part of the Basic plan and up.
Technical ContextAI · show details
LoLLMs (Large Language Model System by parisneo) is a framework for managing and interacting with large language models. The vulnerability stems from CWE-284 (Improper Access Control) where the application uses a predictable or weak cryptographic secret for signing JSON Web Tokens. JWT tokens rely on HMAC-SHA256 or similar algorithms with a shared secret-if the secret has insufficient entropy or is hardcoded, offline dictionary/brute-force attacks using tools like hashcat or jwt_tool can recover it in minutes to hours. Once the signing key is compromised, an attacker can craft arbitrary JWT payloads (setting admin=true, changing user IDs, extending expiration) and sign them with the recovered secret. The application then trusts these forged tokens as legitimate, granting full administrative access without network-based authentication challenges.
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Severity by source
AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
Primary rating from Vendor (huntr_ai) · only source for this CVE.
CVSS VectorVendor: huntr_ai
Lifecycle Timeline
4DescriptionCVE.org
In parisneo/lollms version 2.1.0, the application's session management is vulnerable to improper access control due to the use of a weak secret key for signing JSON Web Tokens (JWT). This vulnerability allows an attacker to perform an offline brute-force attack to recover the secret key. Once the secret key is obtained, the attacker can forge administrative tokens by modifying the JWT payload and resigning it with the cracked secret. This enables unauthorized users to escalate privileges, impersonate the administrator, and gain access to restricted endpoints. The issue is resolved in version 2.2.0.
Executive ViewAI
LoLLMs 2.1.0 contains a critical authentication bypass vulnerability allowing unauthenticated attackers to forge administrator tokens through weak JWT secret key recovery, enabling complete system compromise including user impersonation and unauthorized access to all restricted functionality. Organizations running this version face immediate risk of administrative account takeover and data exposure, requiring emergency patching regardless of current exploitation trends.
Apply vendor patch to LoLLMs 2.2.0 immediately. If patching is delayed: implement network segmentation to restrict unauthenticated access to LoLLMs instances; deploy Web Application Firewall rules to block JWT manipulation attempts; enforce multi-factor authentication at network perimeter; enable comprehensive audit logging of all authentication and token-related events; consider temporary service shutdown until patching is complete.
Threat Intelligence Overview
How this decision was reached
The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.
What every action level means
SSVC AssessmentENISA
Priority Score
Attack Technique
Authentication bypass attacks exploit flaws in the verification mechanisms that control access to systems and applications.
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EUVD-2026-19574
GHSA-9296-v3fr-j92j
NVD
CVE.org
EPSS
Vulnrichment
Exploit-DB