vanna vulnerable to remote code execution caused by prompt injection

In the latest version of vanna-ai/vanna, the vanna.ask function is vulnerable to remote code execution due to prompt injection. The root cause is the lack of a sandbox when executing LLM-generated code, allowing an attacker to manipulate the code executed by the exec function in...

PYSEC-2026-562 vanna vulnerable to remote code execution caused by prompt injection

In the latest version of vanna-ai/vanna, the vanna.ask function is vulnerable to remote code execution due to prompt injection. The root cause is the lack of a sandbox when executing LLM-generated code, allowing an attacker to manipulate the code executed by the exec function in...

Vanna prompt injection code execution

The Vanna library uses a prompt function to present the user with visualized results, it is possible to alter the prompt using prompt injection and run arbitrary Python code instead of the intended visualization code. Specifically - allowing external input to the library’s “ask” method with...

PYSEC-2026-561 Vanna prompt injection code execution

The Vanna library uses a prompt function to present the user with visualized results, it is possible to alter the prompt using prompt injection and run arbitrary Python code instead of the intended visualization code. Specifically - allowing external input to the library’s “ask” method with...

llama-index-core Prompt Injection vulnerability leading to Arbitrary Code Execution

A vulnerability was identified in the executils class of the llamaindex package, specifically within the safeeval function, allowing for prompt injection leading to arbitrary code execution. This issue arises due to insufficient validation of input, which can be exploited to bypass method...

PYSEC-2026-397 llama-index-core Prompt Injection vulnerability leading to Arbitrary Code Execution

A vulnerability was identified in the executils class of the llamaindex package, specifically within the safeeval function, allowing for prompt injection leading to arbitrary code execution. This issue arises due to insufficient validation of input, which can be exploited to bypass method...

PYSEC-2026-448 PandasAI interactive prompt function Remote Code Execution (RCE)

PandasAI uses an interactive prompt function that is vulnerable to prompt injection and run arbitrary Python code that can lead to Remote Code Execution RCE instead of the intended explanation of the natural language processing by the LLM. The security controls of PandasAI 2.4.3 and earlier fail ...

PandasAI interactive prompt function Remote Code Execution (RCE)

PandasAI uses an interactive prompt function that is vulnerable to prompt injection and run arbitrary Python code that can lead to Remote Code Execution RCE instead of the intended explanation of the natural language processing by the LLM. The security controls of PandasAI 2.4.3 and earlier fail ...

CVE-2026-56340

A flaw was found in vLLM. This vulnerability allows a remote attacker to trigger crashes or resource exhaustion, leading to a denial of service DoS. By submitting specially crafted embedding requests with malformed tensor indices, when the prompt-embeds feature is enabled, an attacker could also...

Security--Fidelity Tradeoffs: The Hidden Cost of Prompt Injection Defense

We identify a security-fidelity tradeoff in defending LLMs against indirect prompt injection: defenses resist injected instructions largely by suppressing untrusted text, which corrupts tasks that must preserve it, such as translation and document editing. Attack-success metrics cannot see this,...

Beyond Wireless Security: Covert Communications in Large Language Model-Enabled Edge Networks

Large language model LLM-enabled edge networks LLMENs offer mobile users high-quality and low-latency AI-generated content services in the 6G era. However, unlike typical edge networks, LLMENs present unique security challenges due to the inherent complexity of LLMs, their high computational...

PT-2026-53529

PandasAI uses an interactive prompt function that is vulnerable to prompt injection and run arbitrary Python code that can lead to Remote Code Execution RCE instead of the intended explanation of the natural language processing by the LLM. The security controls of PandasAI 2.4.3 and earlier fail ...

PT-2026-53631

In the latest version of vanna-ai/vanna, the vanna.ask function is vulnerable to remote code execution due to prompt injection. The root cause is the lack of a sandbox when executing LLM-generated code, allowing an attacker to manipulate the code executed by the exec function in...

PT-2026-53630

The Vanna library uses a prompt function to present the user with visualized results, it is possible to alter the prompt using prompt injection and run arbitrary Python code instead of the intended visualization code. Specifically - allowing external input to the library’s “ask” method with...

PT-2026-53562

Summary The memory hooks executor in praisonaiagents passes a user-controlled command string directly to subprocess.run with shell=True at src/praisonai-agents/praisonaiagents/memory/hooks.py lines 303 to 305. No sanitization, no shlex.quote, no character filter, and no allowlist check exists...

PT-2026-53468

Security Vulnerability Report: Prompt to SQL Injection leading to RCE in latest Langroid Affected Scope langroid @localhost:5432/postgres" Create SQL Chat Agent config = SQLChatAgentConfig database uri=DATABASE URI, llm=OpenAIGPTConfig api base=os.getenv"base ur...

Forensic Trajectory Signatures for Agent Memory Poisoning Detection

We discover a behavioral invariant in LLM agents under persistent memory poisoning: in architectures where routing information is retrieved through observable memory-tool invocations, successful attacks require calling memoryrecallfact before emailsendemail, a transition that non-exfiltrating...

PT-2026-53460

In Langchain before 0.0.247, prompt injection allows execution of arbitrary code against the SQL service provided by the chain...

PT-2026-53398

Summary The CAI Cybersecurity AI framework contains multiple argument injection vulnerabilities in its function tools. User-controlled input is passed directly to shell commands via subprocess.Popen with shell=True, allowing attackers to execute arbitrary commands on the host system. Vulnerable...

An Empirical Evaluation of Prompt Injection Vulnerabilities in Large Language Models across Multilingual and Obfuscated Attack Scenarios

Large Language Models LLMs have rapidly evolved, transforming industries by automating complex tasks and generating human-like content. However, as their adoption accelerates, prompt injection vulnerabilities have become increasingly apparent. Malicious actors exploit these weaknesses to generate...