Description

Improper certificate validation vulnerability in HAVELSAN Inc. Sef - AI Chatbot Platform allows Adversary in the Middle (AiTM). This issue affects Sef - AI Chatbot Platform: before 2.1.

Executive Summary

Technical Details

Mitigations

References

Additional Metadata

{
  "score": "7.4",
  "pubDate": "2026-10-02T09:16:44.823Z",
  "pubdate": "2026-10-02T09:16:44.823Z",
  "executiveSummary": "The HAVELSAN Inc. Sef - AI Chatbot Platform contains an improper certificate validation vulnerability that facilitates Adversary-in-the-Middle (AiTM) attacks.\nThis flaw exists in all versions of the Sef - AI Chatbot Platform prior to 2.1.\nThe vulnerability occurs because the application fails to adequately verify the authenticity of SSL/TLS certificates presented by remote endpoints during communication.\nAn attacker positioned on the network path between the Sef platform and its backend services or external APIs can intercept, inspect, or modify sensitive data traffic.\nThe risk is critical as it allows for potential credential theft, information disclosure, and command injection if the chatbot platform relies on these insecure connections for downstream service integration.\nExploitation requires the attacker to have network-level access to intercept traffic, such as through ARP spoofing, DNS poisoning, or control of an intermediate networking device.\nOrganizations using versions earlier than 2.1 are urged to update to the latest version to remediate this communication security flaw.",
  "technicalDetails": "The vulnerability stems from the implementation of insufficient transport layer security validation logic within the Sef - AI Chatbot Platform. Specifically, the application fails to perform rigorous verification of X.509 certificate chains, hostnames, or validity periods when establishing outbound TLS connections.\nIn a standard secure implementation, a client must verify the certificate's signature against a trusted Certificate Authority (CA) store and ensure the Common Name (CN) or Subject Alternative Name (SAN) matches the target hostname. In the vulnerable versions of Sef, the application logic either disables these checks programmatically or fails to enforce them, effectively accepting any certificate provided by a peer.\nAn AiTM attack flow proceeds as follows: First, the attacker intercepts the traffic between the Sef - AI Chatbot Platform and the intended destination server. This is typically achieved via network infrastructure manipulation, such as hijacking internal routing or performing local network sniffing. Second, the attacker presents a fraudulent or self-signed certificate to the Sef platform during the TLS handshake. Third, because the platform lacks proper validation, it accepts the attacker's certificate without error, establishing a secure tunnel directly with the attacker rather than the legitimate destination.\nOnce the tunnel is established, the attacker acts as a transparent proxy. The Sef platform sends requests to what it believes is a legitimate service, but the data is decrypted by the attacker, recorded, and potentially modified. The attacker then forwards the request (or a malicious variant) to the real destination and receives the response. The platform receives the proxied data, unaware that the integrity and confidentiality of the session were compromised at the transport layer.\nThis vulnerability is particularly impactful given the context of an AI chatbot platform, which often interfaces with sensitive backend AI models, databases, and third-party APIs. By successfully intercepting these channels, an attacker could extract sensitive PII, administrative credentials, or proprietary model data. Furthermore, by altering server responses, an attacker could influence the platform's behavior or inject malicious instructions into the AI's processing logic, leading to downstream application compromise."
}