CVE-2026-67355: Not described as a cross-site scripting attack because it involves a misconfiguration of cookie ranges in Guzzle (4th Aug 2026)

Preface: Is there an AI or LLM that uses guzzlehttp? Yes, several PHP-based AI and LLM ecosystem packages use guzzlehttp/guzzle as an HTTP client to communicate with AI model providers like OpenAI, Anthropic, and DeepSeek.

Why do AI and LLM ecosystem packages still use the PHP language today?

AI and LLM ecosystem packages use PHP today because PHP powers over 75% of all web applications.

Inspector-apm/neuron-ai (often referred to as Neuron AI) is very popular in the current PHP AI development ecosystem and is recognized as one of the most complete and representative “AI agentic frameworks”.

Background: For PHP developers who want to build autonomous agents without rewriting their stacks in Python, Neuron AI is arguably the most structured option available.

Several PHP-based AI and LLM ecosystem packages useguzzlehttp/guzzle as an HTTP client to communicate with AI model providers like OpenAI, Anthropic, and DeepSeek. Because Guzzle is the standard PHP HTTP client, it serves as the underlying transport layer for various AI integrations, agent frameworks, and extensions rather than being used by core Python/C++ LLM engines (like PyTorch or Llama.cpp).

Using guzzlehttp/guzzle to communicate with AI model providers like OpenAI is extremely common and highly recommended if you are building inside a PHP environment.

Why It Is Highly Recommended?

Asynchronous Requests: Guzzle supports Promises. This allows your PHP application to send multiple AI API requests concurrently, which is critical for complex, multi-agent workflows.

Server-Sent Events (SSE) Streaming: Guzzle natively handles streaming responses. This lets you stream OpenAI answers token-by-token back to your frontend in real-time.

Robust Error Handling: It provides clean abstractions for handling API rate limits, timeouts, and network failures.

Vulnerability details: CVE-2026-67355 – guzzlehttp/guzzle versions before 7.15.1 fail to preserve host-only cookie scope, storing the request host in the Domain field instead of marking cookies as host-only. Attackers controlling child hosts can receive host-only cookies intended only for parent hosts, potentially disclosing session identifiers and authorization tokens when the same cookie jar is reused across trust boundaries.

Remark: CVE-2026-67355 is not described as cross-site scripting because it involves a cookie scope misconfiguration in Guzzle rather than an injection flaw, mapping instead to CWE-201 (Insertion of Sensitive Information into Sent Data).

Official announcement: Please refer to the link for details – https://www.tenable.com/cve/CVE-2026-67355

Multi-faceted design defect analysis – CVE-2026-7849 (August 3, 2026)

Preface: “Secure by Design” is a flawless theory when studying standards like IEC 62443 or automotive-specific ISO/SAE 21434, but in reality, original equipment manufacturers (OEMs) always compromise due to Bill of Materials (BOM) and production costs.

Background:

•               The Charging Station Side (EVSE): CVE-2026-7849 is strictly an OS Command Injection vulnerability within the Web management interface/REST API of the charging station controller (e.g., Phoenix Contact CHARX SEC-3000) [VDE-2026-008]. It cannot directly access or control the vehicle’s internal CAN bus.

•               The Vehicle Side (EV): The On-Board Charger (OBC) or Electric Vehicle Communication Controller (EVCC) acts as a strict Protocol Gateway between the Control Pilot (CP) line and the vehicle’s internal CAN bus. These two networks are physically and logically air-gapped from each other.

I presume that the design weaknesses of CVE-2026-7849 allow an attacker to compromise the EVSE. From there, they can attempt a secondary pivot attack to cause unknown impacts to the vehicle’s internal CAN Bus (see diagram point 7.1)

How my threat scenario becomes valid?
Stage 1: EVSE Compromise – Exploits CVE-2026-7849 to gain root access on the charging station.
Stage 2: Protocol Pivoting – Uses the station to send malformed digital packets (e.g., ISO 15118 over PLC) via J1772 CP line.
Stage 3: Firmware Exploit – Triggers a zero-day memory corruption / Buffer Overflow bug in the vehicle’s OBC firmware parser.
Stage 4: CAN Bus Injection – Achieves Remote Code Execution (RCE) on the OBC, using its legitimate node access to inject rogue frames onto the Dashboard’s CAN network.

Vulnerability details: Due to improper neutralization of special elements, an unauthenticated remote attacker is able to inject a command into the system configuration which is subsequently executed as root.

Reference: REST (Highest Risk)

  • Why it easily triggers CWE-77: REST APIs fundamentally handle diverse, text-based data inputs (JSON, XML, URL parameters, form fields) that often directly influence backend operations.
  • The Trigger Mechanism: Many embedded devices and IoT web panels use REST endpoints to accept configuration changes (e.g., setting an IP address, updating a hostname, or running a network ping). If the developer passes these text inputs directly into a backend operating system shell command (like system() or exec()) without strict input sanitization, an attacker can append command separators (like ;, &&, or |) to execute malicious code.

Official announcement: For details, please refer to link for details – https://www.tenable.com/cve/CVE-2026-7849