CVE-2026-55976 Apache Hive Avro SerDe SSRF Vulnerability – Detection, Impact & Remediation

Executive Summary

A critical Server-Side Request Forgery (SSRF) vulnerability has been identified in Apache Hive’s Avro Serializer/Deserializer (SerDe) component, designated CVE-2026-55976. This flaw allows authenticated users with basic CREATE TABLE privileges to configure malicious schema URLs that trigger unvalidated outbound requests from the Hive server process.

When an affected Avro table is queried, the Hive server automatically fetches the schema from an attacker-controlled URL, potentially exposing cloud metadata endpoints, internal network services, and local files. The vulnerability affects all Apache Hive versions prior to 4.2.1 and carries a high severity rating due to its confidentiality impact.

Immediate action required: Organizations should upgrade to Apache Hive 4.2.1 or later without delay, particularly those operating in cloud environments.

What Is CVE-2026-55976?

Vulnerability Overview

CVE-2026-55976 is a Server-Side Request Forgery vulnerability in Apache Hive’s Avro SerDe schema resolution mechanism. The flaw stems from insufficient validation of the avro.schema.url table property, which specifies where the Hive server should retrieve Avro schema definitions during table operations.

An authenticated attacker can exploit this by:

1. Creating or modifying an Avro-backed external table
2. Setting the avro.schema.url property to point to an arbitrary network location
3. Triggering schema resolution by executing a SELECT query
4. Causing the Hive server to make an unvalidated outbound request to the attacker-specified URL

The vulnerability is particularly dangerous because schema resolution occurs automatically during normal query execution, requiring no special privileges or administrative intervention.

Attack Vector & Trigger Mechanism

Attack Vector: Network-based, requires authentication
Trigger: Execution of SELECT query against a malicious Avro table
Privilege Requirement: CREATE TABLE (DDL) permission

The attack chain unfolds as follows:

1. Attacker authenticates to HiveServer2 or Metastore with valid credentials
2. Attacker creates an external table with Avro format, specifying a malicious avro.schema.url
3. Attacker (or any user with SELECT permission) executes a query against the table
4. Hive server initiates schema resolution and makes an HTTP/HTTPS/FTP request to the specified URL
5. Response data or error messages may leak sensitive information back to the attacker

Supported Protocol Schemes

The vulnerability supports multiple protocol schemes, expanding the attack surface:

Affected Systems & Versions

Vulnerable Apache Hive Versions

All Apache Hive versions prior to 4.2.1 are affected by this vulnerability. This includes:

• Apache Hive 4.2.0 and earlier
• Apache Hive 4.1.x series
• Apache Hive 4.0.x series
• Apache Hive 3.x series
• Apache Hive 2.x series

Organizations running any of these versions in production environments face active risk.

Patched Release Information

Fixed Version: Apache Hive 4.2.1 and later

The patch introduces strict validation of the avro.schema.url property, restricting schema fetches to approved locations and blocking requests to sensitive endpoints (such as cloud metadata services).

Component Scope: Avro SerDe

The vulnerability is specific to the Avro SerDe component. Other SerDe implementations (Parquet, ORC, JSON, etc.) are not affected. However, any Hive deployment that supports Avro tables is vulnerable if running an affected version.

How the Vulnerability Works

Schema Resolution Process

Apache Hive’s Avro SerDe uses a two-stage schema resolution process:

1. Schema Discovery: When a table is created with STORED AS AVRO, Hive checks for schema information
2. Schema Fetch: If avro.schema.url is specified, Hive fetches the schema from the provided URL
3. Schema Parsing: The fetched content is parsed as an Avro schema definition
4. Query Execution: The schema is used to deserialize data during query operations

Unvalidated URL Handling

The vulnerability exists because Hive does not validate the avro.schema.url parameter before making the request. Specifically:

• No URL scheme validation: Any protocol is accepted
• No destination validation: No checks against internal IP ranges or metadata endpoints
• No timeout enforcement: Requests may hang indefinitely
• No response validation: Any HTTP response is treated as a valid schema

This means an attacker can specify URLs pointing to:

• Internal network services (10.0.0.0/8, 172.16.0.0/12, 192.168.0.0/16)
• Cloud metadata endpoints (169.254.169.254)
• Local file system paths (file:///etc/passwd)
• External attacker-controlled servers

Automatic Request Execution During Queries

The critical aspect of this vulnerability is that schema fetches occur automatically during query execution. An attacker does not need to:

• Execute special commands
• Have write access to the table’s data location
• Possess administrative privileges
• Trigger manual schema refresh operations

Simply executing a SELECT query against the malicious table causes the Hive server to fetch the schema, making this a low-friction attack vector.

Real-World Attack Scenarios

Cloud Metadata & IAM Token Extraction

Scenario: An attacker in a cloud environment (AWS, Azure, GCP) exploits CVE-2026-55976 to extract temporary IAM credentials.

Attack Steps:

CREATE EXTERNAL TABLE malicious_avro (
  id INT,
  data STRING
)
STORED AS AVRO
LOCATION '/tmp/data'
TBLPROPERTIES (
  'avro.schema.url'='http://169.254.169.254/latest/meta-data/iam/security-credentials/hive-role'
);
SELECT * FROM malicious_avro LIMIT 1;

Outcome: The Hive server makes an HTTP request to the AWS metadata endpoint, retrieving temporary credentials. Error messages or logs may expose these credentials to the attacker.

Impact: Lateral movement within the cloud environment, privilege escalation, data exfiltration.

Internal Network Service Enumeration

Scenario: An attacker maps internal network topology and discovers hidden administrative interfaces.

Attack Steps:

CREATE EXTERNAL TABLE enum_internal (id INT)
STORED AS AVRO
LOCATION '/tmp/data'
TBLPROPERTIES (
  'avro.schema.url'='http://internal-admin-panel.local:8080/api/status'
);
SELECT * FROM enum_internal;

Outcome: By observing response times, error messages, and HTTP status codes, the attacker can:

• Identify active internal hosts
• Discover open ports and services
• Interact with unauthenticated internal APIs
• Gather intelligence for further attacks

Impact: Network reconnaissance, discovery of vulnerable internal services, preparation for lateral movement.

Local File System Access via file:// URIs

Scenario: An attacker reads sensitive configuration files from the Hive server’s local file system.

Attack Steps:

CREATE EXTERNAL TABLE read_local_files (id INT)
STORED AS AVRO
LOCATION '/tmp/data'
TBLPROPERTIES (
  'avro.schema.url'='file:///etc/passwd'
);
SELECT * FROM read_local_files;

Outcome: The Hive server attempts to read /etc/passwd as an Avro schema. While the file format won’t parse as valid Avro, error messages may leak file contents or reveal the file’s existence and permissions.

Impact: Information disclosure, credential exposure if configuration files contain secrets, system enumeration.

Who Can Exploit This Vulnerability?

Required Attacker Privileges

To successfully exploit CVE-2026-55976, an attacker must possess:

1. Network Connectivity: Access to HiveServer2 or Metastore endpoints (typically restricted to internal networks)
2. Valid Authentication: Legitimate Hive user credentials
3. DDL Privileges: CREATE TABLE or ALTER TABLE permission

These requirements are typically met by:

• Legitimate employees with data access
• Compromised user accounts
• Insider threats
• Attackers who have gained initial access to the network

Authentication & DDL Requirements

The vulnerability requires authenticated access. Unauthenticated users cannot exploit it. However, the required privilege level is minimal:

• Standard database users with CREATE TABLE rights can exploit this
• No superuser or administrative privileges needed
• No special Hive-specific roles required

In many organizations, these privileges are broadly granted to data engineers and analysts, expanding the potential attacker pool.

Non-Requirements: Admin Rights & Write Access

Importantly, the following are NOT required to exploit this vulnerability:

This low barrier to exploitation makes CVE-2026-55976 particularly dangerous in multi-tenant or shared Hive environments.

Risk Assessment & Severity

CVSS Classification & Impact Level

CVSS v3.1 Score: 7.5 (High)

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

Breakdown:

• Attack Vector (AV:N): Network-based, remotely exploitable
• Attack Complexity (AC:L): Low complexity, no special conditions required
• Privileges Required (PR:L): Low privileges (authenticated user with DDL rights)
• User Interaction (UI:N): No user interaction required
• Scope (S:U): Unchanged (impact limited to Hive server)
• Confidentiality (C:H): High impact on confidentiality
• Integrity (I:N): No integrity impact
• Availability (A:N): No availability impact

Confidentiality Exposure Scope

The vulnerability directly impacts confidentiality through information disclosure:

1. Cloud Metadata Exposure

• Instance metadata (region, availability zone, instance ID)
• IAM role credentials and temporary tokens
• SSH keys and security group information

1. Internal Network Information

• Service discovery and enumeration
• Internal IP addresses and hostnames
• Open ports and service versions
• API endpoints and authentication mechanisms

1. Local File Disclosure

• Configuration files with embedded credentials
• Application secrets and API keys
• System information (/etc/passwd, /etc/hosts)
• Hive metastore connection strings

Business Risk Implications

For Cloud Deployments:

• Credential theft leading to unauthorized cloud resource access
• Data exfiltration from cloud storage (S3, Azure Blob, GCS)
• Lateral movement to other cloud services
• Compliance violations (HIPAA, PCI-DSS, GDPR)

For On-Premises Deployments:

• Network reconnaissance enabling further attacks
• Exposure of internal service architecture
• Credential compromise for internal systems
• Potential for supply chain attacks if Hive is used in data pipelines

For All Deployments:

• Reputational damage from data breaches
• Regulatory fines and legal liability
• Operational disruption from incident response
• Loss of customer trust

Detection & Identification Methods

Metastore Metadata Auditing

The most direct detection method is to audit Hive metastore tables for suspicious avro.schema.url properties.

SQL Query to Identify Suspicious Tables:

SELECT 
  t.TBL_NAME,
  t.TBL_TYPE,
  p.PARAM_KEY,
  p.PARAM_VALUE,
  t.CREATE_TIME
FROM TBLS t
JOIN TABLE_PARAMS p ON t.TBL_ID = p.TBL_ID
WHERE p.PARAM_KEY = 'avro.schema.url'
  AND (
    p.PARAM_VALUE LIKE 'http://%'
    OR p.PARAM_VALUE LIKE 'https://%'
    OR p.PARAM_VALUE LIKE 'file://%'
    OR p.PARAM_VALUE LIKE 'ftp://%'
    OR p.PARAM_VALUE LIKE '%169.254.169.254%'
    OR p.PARAM_VALUE LIKE '%metadata%'
  )
ORDER BY t.CREATE_TIME DESC;

Red Flags to Look For:

• URLs pointing to 169.254.169.254 (AWS metadata)
• URLs pointing to metadata.google.internal (GCP metadata)
• URLs pointing to 169.254.169.254:80 (Azure metadata)
• file:// URLs pointing to sensitive locations
• URLs pointing to internal IP ranges (10.0.0.0/8, 172.16.0.0/12, 192.168.0.0/16)
• Recently created tables with unusual schema URLs
• Tables created by non-standard service accounts

Log Analysis Techniques

HiveServer2 Logs:

Search for patterns indicating schema resolution attempts:

grep -i "avro.schema.url" /var/log/hive/hiveserver2.log
grep -i "schema.*resolution\|fetch.*schema" /var/log/hive/hiveserver2.log
grep -i "http.*request\|outbound.*connection" /var/log/hive/hiveserver2.log

Metastore Logs:

grep -i "CREATE TABLE.*AVRO\|ALTER TABLE.*avro.schema.url" /var/log/hive/metastore.log
grep -i "schema.*fetch\|url.*validation" /var/log/hive/metastore.log

Correlation Analysis:

Look for patterns where:

1. A CREATE TABLE or ALTER TABLE statement modifies avro.schema.url
2. Followed shortly by a SELECT query on the same table
3. Followed by unusual network activity or error messages

Example Log Signature:

[timestamp] CREATE EXTERNAL TABLE suspicious_table ... TBLPROPERTIES ('avro.schema.url'='http://169.254.169.254/...')
[timestamp+seconds] SELECT * FROM suspicious_table
[timestamp+seconds] ERROR: Connection refused | Timeout | Invalid schema format

Network & Cloud Telemetry Monitoring

VPC Flow Logs (AWS):

Monitor for outbound connections from Hive nodes to:

• 169.254.169.254:80 (AWS metadata)
• Internal IP ranges
• Unusual external IPs

CloudTrail / Audit Logs:

Look for:

• Metadata service access from Hive instance roles
• Credential usage from temporary tokens
• Unusual API calls shortly after Hive query execution

Network IDS/IPS Alerts:

Configure rules to detect:

• HTTP requests to 169.254.169.254
• Connections to internal services from Hive nodes
• file:// URI access attempts

Syslog/Auditd Monitoring:

auditctl -w /etc/passwd -p wa -k hive_file_access
auditctl -w /etc/hive-site.xml -p wa -k hive_config_access

Immediate Remediation Steps

Upgrade to Apache Hive 4.2.1

This is the primary and most critical remediation step.

Upgrade Process:

1. Backup Current Installation:

   cp -r /opt/hive /opt/hive.backup.$(date +%Y%m%d)

1. Download Hive 4.2.1:

   wget https://archive.apache.org/dist/hive/hive-4.2.1/apache-hive-4.2.1-bin.tar.gz
   tar -xzf apache-hive-4.2.1-bin.tar.gz

1. Stop Hive Services:

   systemctl stop hiveserver2
   systemctl stop hive-metastore

1. Replace Hive Installation:

   rm -rf /opt/hive
   mv apache-hive-4.2.1-bin /opt/hive
   chown -R hive:hive /opt/hive

1. Restart Services:

   systemctl start hive-metastore
   systemctl start hiveserver2

1. Verify Installation:

   schematool -dbType mysql -info
   beeline -u jdbc:hive2://localhost:10000 -e "SELECT version();"

Testing: After upgrade, verify that:

• Hive services start without errors
• Existing tables are accessible
• Queries execute normally
• Metastore connectivity is functional

Restrict DDL Privileges

While upgrading, implement principle of least privilege for DDL operations.

Audit Current Permissions:

SHOW GRANT USER <username>;
SHOW GRANT ROLE <rolename>;

Revoke Unnecessary CREATE TABLE Rights:

REVOKE CREATE ON DATABASE <dbname> FROM USER <username>;
REVOKE CREATE ON DATABASE <dbname> FROM ROLE <rolename>;

Grant Only to Trusted Accounts:

GRANT CREATE ON DATABASE <dbname> TO USER <trusted_admin>;
GRANT CREATE ON DATABASE <dbname> TO ROLE data_engineers;

Implement Role-Based Access Control:

CREATE ROLE data_analyst;
GRANT SELECT ON DATABASE <dbname> TO ROLE data_analyst;
CREATE ROLE data_engineer;
GRANT SELECT, CREATE ON DATABASE <dbname> TO ROLE data_engineer;
GRANT ROLE data_analyst TO USER <username>;

Implement Network Egress Controls

Restrict outbound network traffic from Hive nodes to prevent SSRF exploitation.

Firewall Rules (iptables/firewalld):

# Block outbound to metadata endpoints
iptables -A OUTPUT -d 169.254.169.254 -j DROP
iptables -A OUTPUT -d 169.254.169.253 -j DROP
# Block outbound to internal ranges (if Hive should not access them)
iptables -A OUTPUT -d 10.0.0.0/8 -j DROP
iptables -A OUTPUT -d 172.16.0.0/12 -j DROP
iptables -A OUTPUT -d 192.168.0.0/16 -j DROP
# Allow only necessary outbound (HDFS, S3, etc.)
iptables -A OUTPUT -d <hdfs_namenode_ip> -p tcp --dport 8020 -j ACCEPT
iptables -A OUTPUT -d <s3_endpoint> -p tcp --dport 443 -j ACCEPT

Security Group Rules (AWS):

Outbound Rules:
- Deny all traffic to 169.254.169.254
- Deny all traffic to internal IP ranges (unless necessary)
- Allow only to approved external services (S3, RDS, etc.)

Network Policy (Kubernetes):

apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
  name: hive-egress-policy
spec:
  podSelector:
    matchLabels:
      app: hiveserver2
  policyTypes:
  - Egress
  egress:
  - to:
    - namespaceSelector: {}
    ports:
    - protocol: TCP
      port: 8020  # HDFS
  - to:
    - podSelector:
        matchLabels:
          app: metastore
    ports:
    - protocol: TCP
      port: 9083

Long-Term Security Controls

Access Management Best Practices

Implement Principle of Least Privilege:

• Grant DDL privileges only to service accounts and trusted administrators
• Use role-based access control (RBAC) for all database operations
• Regularly audit and revoke unnecessary permissions
• Implement separation of duties (developers cannot deploy to production)

Multi-Factor Authentication:

# Configure Kerberos for Hive authentication
# In hive-site.xml:
<property>
  <name>hive.server2.authentication</name>
  <value>KERBEROS</value>
</property>
<property>
  <name>hive.server2.authentication.kerberos.principal</name>
  <value>hive/_HOST@REALM</value>
</property>

Service Account Management:

• Use dedicated service accounts for Hive processes
• Rotate credentials regularly
• Monitor service account activity
• Disable unused service accounts

Continuous Monitoring & Alerting

Set Up Real-Time Alerts:

# Prometheus alert rule
- alert: SuspiciousAvroSchemaURL
  expr: |
    count(
      hive_table_params{param_key="avro.schema.url", 
      param_value=~".*169\.254\.169\.254.*|.*file://.*"}
    ) > 0
  for: 1m
  annotations:
    summary: "Suspicious Avro schema URL detected"
    description: "Table {{ $labels.table_name }} has suspicious schema URL"

Log Aggregation & Analysis:

# ELK Stack configuration
# Filebeat input for Hive logs
filebeat.inputs:
- type: log
  enabled: true
  paths:
    - /var/log/hive/*.log
  fields:
    service: hive
  processors:
    - add_kubernetes_metadata: ~
# Elasticsearch index pattern
hive-logs-*
# Kibana alert
{
  "name": "Avro SSRF Detection",
  "condition": {
    "query": "service:hive AND (avro.schema.url OR metadata OR 169.254)"
  },
  "actions": ["send_email", "create_incident"]
}

Metrics to Monitor:

• Number of tables with external schema URLs
• Frequency of schema resolution failures
• Outbound connection attempts from Hive nodes
• DDL operations by user and timestamp
• Query execution patterns on Avro tables

Configuration Hardening

Hive Configuration (hive-site.xml):

<!-- Disable external schema URLs entirely (if not needed) -->
<property>
  <name>hive.avro.schema.url.allowed</name>
  <value>false</value>
</property>
<!-- Whitelist allowed schema URL patterns -->
<property>
  <name>hive.avro.schema.url.whitelist</name>
  <value>^https://internal-schema-registry\.company\.com/.*</value>
</property>
<!-- Enforce HTTPS for schema URLs -->
<property>
  <name>hive.avro.schema.url.require.https</name>
  <value>true</value>
</property>
<!-- Set connection timeout to prevent hanging -->
<property>
  <name>hive.avro.schema.url.timeout.ms</name>
  <value>5000</value>
</property>
<!-- Disable file:// protocol -->
<property>
  <name>hive.avro.schema.url.allow.file.protocol</name>
  <value>false</value>
</property>

Metastore Configuration:

<!-- Enable audit logging -->
<property>
  <name>hive.metastore.event.listeners</name>
  <value>org.apache.hadoop.hive.metastore.events.LoggingEventListener</value>
</property>
<!-- Restrict table property modifications -->
<property>
  <name>hive.metastore.disallow.incompatible.col.type.changes</name>
  <value>true</value>
</property>

Frequently Asked Questions

Does the attacker need administrator or superuser rights to exploit CVE-2026-55976?

No. An ordinary authenticated Hive user with standard CREATE TABLE (DDL) privileges can set the malicious avro.schema.url property and execute the attack. Superuser or administrative rights are not required.

This is a critical aspect of the vulnerability’s severity—it can be exploited by any user with basic database privileges, not just privileged accounts.

Is write access to the table’s underlying data location required?

No. The vulnerability relies entirely on the schema resolution path specified by the avro.schema.url table property, not on write access to the physical data directory specified in the LOCATION clause.

An attacker can exploit this vulnerability even if they have no write permissions to the table’s data storage location. The SSRF is triggered by the schema URL property alone.

Can non-creator users trigger the vulnerability?

Yes. While the table creator can trigger the fetch by querying their own table, any other authenticated user who has been granted SELECT permissions on the table will also trigger the schema fetch when executing a query against it.

This means a malicious table creator can set a trap for other users, and those users will unknowingly trigger the SSRF when they query the table.

Are external tables required to exploit this issue?

External table functionality is typically required in practice. External tables are enabled by default in most standard Apache Hive deployments. The vulnerability specifically affects external Avro tables because they support the avro.schema.url property.

Managed tables can also be affected if they are configured with Avro format and external schema URLs.

What cloud metadata endpoints are at risk?

Attackers can target link-local metadata addresses such as 169.254.169.254 to extract cloud instance metadata, temporary IAM credentials, and identity tokens. Specific endpoints vary by cloud provider:

AWS:

• http://169.254.169.254/latest/meta-data/
• http://169.254.169.254/latest/meta-data/iam/security-credentials/

Azure:

• http://169.254.169.254/metadata/instance?api-version=2021-02-01

GCP:

• http://metadata.google.internal/computeMetadata/v1/

How quickly should we patch this vulnerability?

Immediately. This is a high-severity SSRF vulnerability affecting confidentiality. Upgrade to Apache Hive 4.2.1 or later without delay, especially in cloud environments where metadata endpoint exploitation is a significant risk.

Organizations should prioritize this patch above routine maintenance windows and apply it as soon as testing confirms compatibility with their environment.

References

• CVE Identifier: CVE-2026-55976
• Vulnerability Type: CWE-918 (Server-Side Request Forgery)
• Apache Hive Release Notes: Apache Hive 4.2.1 Release Documentation
• CVSS Calculator: NVD CVSS v3.1 Calculator
• SSRF Prevention: OWASP Server-Side Request Forgery

Document Classification: Security Advisory
Last Updated: 2024
Next Review: Upon release of Apache Hive 4.2.2 or security updates