CVE-2025-69217: coturn TURN/STUN Server Predictable Random Number Generation Vulnerability

Vulnerability Overview

CVE Identifier: CVE-2025-69217
Affected Software: coturn (TURN / STUN Server Implementation)
Vulnerable Versions: 4.6.2-r5 through 4.7.0-r4
Fixed Version: Versions including commit 11fc465f4bba70bb0ad8aae17d6c4a63a29917d9
CVSS v3.1 Score: 7.5 (HIGH)
Severity Rating: HIGH

CVSS Vector Breakdown

Attack Vector (AV): Network
Attack Complexity (AC): Low
Privileges Required (PR): None
User Interaction (UI): None
Scope (S): Unchanged
Confidentiality Impact (C): High
Integrity Impact (I): High
Availability Impact (A): Medium

Exploitability: HIGH – exploitable remotely without authentication
Exploit Availability: No public weaponized exploit released, but exploitation techniques are well understood and reproducible; working PoCs are feasible and likely circulating in research circles

Vulnerability Description

coturn, a widely used open-source TURN/STUN server for NAT traversal in WebRTC, VoIP, IoT, and real-time communication systems, contains a serious flaw in its random number generation logic.

Due to an internal refactoring change, coturn stopped using OpenSSL’s cryptographically secure random number generator (RAND_bytes) and instead began using the standard C library’s random() function on non-Windows platforms.

This change directly impacted two security-critical mechanisms:

Authentication Nonce Generation
Relay Port Randomization

The random() function is not designed for security use. It produces deterministic output that can be predicted once enough values are observed. In coturn’s case, attackers can remotely collect enough outputs (nonces) to reconstruct the generator’s internal state and predict future values with full accuracy.

Once that happens, TURN authentication guarantees break down entirely.

Technical Deep Dive

Root Cause Analysis

The libc random() function uses a predictable pseudorandom algorithm with a small internal state. Unlike cryptographically secure generators, it provides no resistance to state reconstruction.

Key characteristics:

Deterministic output
Small internal state (often 128–256 bytes)
Predictable once enough outputs are known
Not safe for cryptographic purposes

coturn reused this weak generator for:

Nonce values used in TURN authentication
Relay port selection for client allocations

This created a single shared weakness affecting both authentication and network isolation.

Exploitation Mechanics

Phase 1 – Nonce Harvesting

An attacker sends a burst of unauthenticated TURN ALLOCATE requests.
Each request results in a 401 Unauthorized response containing a freshly generated nonce.

By sending approximately 50 sequential requests, the attacker can collect enough nonce values to analyze the generator’s behavior.

This step:

Requires no credentials
Requires no prior access
Can be performed entirely over the network

Phase 2 – PRNG State Reconstruction

Using the collected nonce values, the attacker applies mathematical and statistical techniques to reconstruct the internal state of the random() generator.

Once reconstructed:

All future nonce values are predictable
The attacker can calculate past, current, and future outputs
The attacker no longer needs server responses to authenticate

This effectively removes the randomness from the authentication process.

Phase 3 – Authentication Without Receiving Responses

Normally, TURN authentication works as follows:

Client sends request
Server responds with nonce
Client computes authentication hash
Client retries request with valid credentials and nonce

With nonce prediction:

Step 2 is no longer needed
The attacker predicts the nonce ahead of time
Authentication hashes can be computed offline
Requests succeed even if responses are never received

This enables authenticated requests from spoofed IP addresses, since the attacker does not need to see the server’s replies.

Phase 4 – Relay Port Prediction

Relay port allocation uses the same weak random number generator.

Once the attacker knows the generator’s state:

The next relay port can be predicted exactly
Future unused ports can be calculated
Port selection becomes deterministic

This allows attackers to:

Preemptively bind to future relay ports
Intercept or hijack relay traffic
Exhaust relay port pools deliberately

Real-World Attack Scenarios

IoT Communication Hijacking

Many IoT deployments:

Use TURN servers for NAT traversal
Rely on shared or hardcoded credentials

An attacker can:

Predict nonces
Authenticate as an IoT device
Allocate unauthorized relays
Redirect or intercept telemetry, video, or control traffic

WebRTC Media Interception

For WebRTC platforms using coturn:

Attackers can predict relay ports assigned to users
Position themselves to intercept call traffic
Enable man-in-the-middle scenarios at the relay level

While DTLS/SRTP still provides encryption, this attack significantly weakens the overall trust model and can be combined with other weaknesses.

Enterprise VoIP Abuse

In enterprise environments, this vulnerability enables:

Call interception and eavesdropping
Relay-based denial of service
Toll fraud through unauthorized relays
Stealthy traffic manipulation inside trusted networks

MITRE ATT&CK Mapping

Initial Access

T1190 – Exploit Public-Facing Application

Credential Access

T1110 – Authentication Abuse (nonce prediction enabling bypass)

Defense Evasion

T1562.001 – Bypass IP-based controls via spoofing

Network Boundary Bridging

T1599 – TURN relay misuse

Collection

T1040 – Network Sniffing
T1113 – Screen Capture (WebRTC screen sharing contexts)

Command and Control

T1090.001 – Internal Proxy via TURN relays
T1572 – Protocol Tunneling

Proof of Concept (Conceptual)

Exploitation Workflow (High-Level)

Nonce Collection

for i in 1..50:
  send unauthenticated TURN Allocate request
  extract nonce from 401 response

State Reconstruction

analyze collected nonces
solve PRNG internal state
verify by predicting next nonce

Authentication Bypass

predict future nonce
generate authentication hash using known credentials
send authenticated request (spoofed IP possible)
allocation succeeds

No malware, shellcode, or memory corruption is required.

Detection Indicators

Behavioral Indicators

50+ unauthenticated allocation requests in short timeframes
Authentication success without a prior nonce challenge
Allocations from spoofed or rapidly changing IP addresses
Relay ports showing low entropy or predictable sequencing

Detection Strategies

Required Log Sources

Primary

coturn application logs
Firewall logs (UDP/TCP 3478)
Network flow telemetry (NetFlow/IPFIX)

Secondary

Authentication logs
IDS/IPS telemetry
Bandwidth and session monitoring tools

Example Detection Rules

Rapid Nonce Harvesting

Condition:
  >=50 unauthenticated Allocate requests
  from same source IP
  within 60 seconds

Authentication Without Challenge

Condition:
  authenticated Allocate request
  without prior 401 nonce challenge
  within last 5 minutes

Predictable Port Allocation

Condition:
  relay ports show sequential or low-entropy patterns

Remediation and Mitigation

Official Patch

The vulnerability has been officially fixed by the coturn maintainers.

Patch Details

Fix Commit ID: 11fc465f4bba70bb0ad8aae17d6c4a63a29917d9
Project: coturn
Fix Type: Replacement of weak libc random() usage with cryptographically secure random number generation and separation of RNG usage for security-sensitive operations.

Official Patch Link

The fix can be reviewed and applied directly from the coturn source repository at the following official commit:

https://github.com/coturn/coturn/commit/11fc465f4bba70bb0ad8aae17d6c4a63a29917d9

Immediate Mitigations (If Patching Is Delayed)

Network Controls

Rate-limit allocation requests (e.g., ≤10/min/IP)
Restrict TURN access by IP where feasible
Deploy IDS rules for nonce harvesting patterns

Operational Controls

Rotate TURN credentials immediately
Reduce nonce lifetime
Restart coturn periodically to reset PRNG state (temporary only)

Post-Patch Hardening Best Practices

Use TLS/DTLS for all TURN traffic
Enforce strong, unique credentials per client
Avoid shared IoT credentials
Enable verbose logging
Monitor relay port entropy regularly
Apply strict session lifetime limits

Impact Assessment

Confidentiality: High – potential interception of communications
Integrity: High – spoofed allocations and routing manipulation
Availability: Medium – relay exhaustion and service disruption

Business Impact

Regulatory exposure (GDPR, HIPAA)
Loss of trust in communication platforms
Financial loss from VoIP toll fraud
Espionage and data leakage risks

Conclusion

CVE-2025-69217 undermines the foundational security assumptions of TURN authentication by replacing cryptographic randomness with predictable pseudorandom behavior. Once exploited, attackers can bypass authentication, spoof IP addresses, and predict relay port assignments with precision.

Because exploitation is remote, low-complexity, and highly reliable once initiated, this vulnerability should be treated as a high-priority security issue. All affected deployments should be patched immediately and monitored closely for signs of abuse.