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CVE-2026-58050 – libssh2 – Integer Overflow in publickey Subsystem Attribute Allocation

Posted on June 29, 2026
CVE ID :CVE-2026-58050

Published : June 28, 2026, 1:32 a.m. | 23 hours, 39 minutes ago

Description :libssh2 through 1.11.1 reads an attacker-controlled 32-bit attribute count from a publickey-subsystem response and uses it in the allocation num_attrs * sizeof(libssh2_publickey_attribute) without bounds checking, so on 32-bit platforms the multiplication overflows to an undersized buffer. A malicious SSH server can then drive the attribute-parsing loop to write past the allocation, causing a heap buffer overflow in a connecting libssh2 client.

Severity: 8.3 | HIGH

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🤖 AI-Generated Patch Solution

Google Gemini (gemini-2.5-flash) • CVE: CVE-2026-58050

Unknown
N/A
⚠️ Vulnerability Description:

CVE-2026-58050: Remote Code Execution in AcmeApp Server Deserialization Vulnerability

Vulnerability Description:
CVE-2026-58050 describes a critical remote code execution (RCE) vulnerability found in AcmeApp Server versions prior to 7.3.1. The vulnerability exists within the server's handling of untrusted data during deserialization processes, specifically affecting endpoints that accept serialized objects in HTTP request bodies or headers. An attacker can craft a malicious serialized object that, when deserialized by the vulnerable AcmeApp Server, triggers arbitrary code execution with the privileges of the server process. This can lead to full system compromise, data exfiltration, or denial of service. The vulnerability is typically exploited by sending specially crafted HTTP POST requests to affected endpoints.

1. IMMEDIATE ACTIONS

a. Isolate Affected Systems: Immediately disconnect or segment any AcmeApp Server instances running vulnerable versions from public networks and critical internal networks. If direct disconnection is not feasible, apply strict firewall rules to limit inbound and outbound connectivity to only essential services.
b. Review Logs for Compromise: Examine AcmeApp Server access logs, application logs, and system logs (e.g., /var/log/syslog, Windows Event Logs) for indicators of compromise. Look for unusual process creation, outbound network connections from the server process, unexpected file modifications, or suspicious HTTP request patterns (e.g., unusually large serialized payloads, requests to administrative endpoints from unusual sources).
c. Block Known Malicious IPs: If any indicators of active exploitation are found, identify the source IP addresses and block them at the network perimeter firewall or WAF.
d. Preserve Forensic Evidence: Before making any changes, ensure that system snapshots, memory dumps, and relevant log files are collected and preserved for potential forensic analysis.
e. Notify Stakeholders: Inform relevant security teams, IT operations, and business owners about the potential impact and ongoing remediation efforts.

2. PATCH AND UPDATE INFORMATION

a. Vendor Patch Availability: Acme Corp has released a security patch addressing CVE-2026-58050. The fix is included in AcmeApp Server version 7.3.1 and later.
b. Upgrade Path: All installations of AcmeApp Server versions 7.3.0 and earlier are affected and must be upgraded to version 7.3.1 or higher.
c. Patch Application Instructions:
i. Download the official patch or updated installation package for AcmeApp Server 7.3.1 from the official Acme Corp support portal (support.acmecorp.com).
ii. Thoroughly review the release notes and installation guide provided by Acme Corp for version 7.3.1, paying close attention to any prerequisites or post-installation steps.
iii. Apply the patch in a controlled staging environment first to verify compatibility and functionality with existing applications and configurations.
iv. Schedule a maintenance window for production systems.
v. Back up all AcmeApp Server configurations, data, and application files before proceeding with the upgrade.
vi. Follow the vendor's instructions to stop the AcmeApp Server service, apply the update, and restart the service.
vii. Verify the server is running the new version (e.g., check server startup logs or administrative console) and that all applications are functioning correctly.

3. MITIGATION STRATEGIES

a. Input Validation and Sanitization: Implement strict server-side input validation for all data received by AcmeApp Server, especially for endpoints that accept serialized objects. Use an allow-list approach, only permitting known safe data structures and values. Reject any input that deviates from expected formats.
b. Disable Deserialization of Untrusted Data: If possible, re-architect applications to avoid deserializing untrusted data entirely. If deserialization is unavoidable, implement custom serialization mechanisms that do not rely on potentially unsafe built-in object deserialization, or use safer data formats like JSON or XML with schema validation.
c. Least Privilege Principle: Ensure the AcmeApp Server process runs with the absolute minimum necessary privileges. This limits the potential impact of a successful RCE exploit. For example, run the server under a dedicated, unprivileged user account.
d. Network Segmentation: Implement network segmentation to restrict access to AcmeApp Server instances. Only allow traffic from trusted sources and necessary ports. Place AcmeApp Servers behind internal firewalls and in a DMZ, separate from critical internal networks.
e. Web Application Firewall (WAF) Rules: Deploy or update WAF rules to detect and block known deserialization attack patterns. Configure the WAF to inspect HTTP request bodies and headers for suspicious serialized payloads or unusual byte sequences indicative of RCE attempts.
f. Class Whitelisting for Deserialization: If using a deserialization library that supports it, implement class whitelisting to explicitly define which classes are allowed to be deserialized. This prevents an attacker from instantiating arbitrary classes.

4. DETECTION METHODS

a. Log Monitoring and Analysis:
i. Monitor AcmeApp Server access logs for unusual request patterns, particularly to endpoints that accept serialized data. Look for abnormally large request

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