Evidence used
- No CISA KEV confirmation is currently recorded.
- EPSS is 0.57% for the current model date.
BlackTreeCVE IntelligenceAWS · strands-agents-tools
High technical severity; prioritise exposed affected systems while verifying vendor guidance.
High technical severity; prioritise exposed affected systems while verifying vendor guidance.
Patch availableA prompt injection vulnerability in the shell tool in Amazon Strands Agents Tools before 0.8.0 might allow remote actors to execute arbitrary operating system commands on the agent's host via a crafted prompt that sets the non_interactive parameter to true, bypassing the human consent gate. To remediate this issue, users should upgrade to version 0.8.0.
A prompt injection vulnerability in the shell tool in Amazon Strands Agents Tools before 0.8.0 might allow remote actors to execute arbitrary operating system commands on the agent's host via a crafted prompt that sets the non_interactive parameter to true, bypassing the human consent gate. To remediate this issue, users should upgrade to version 0.8.0.
The product uses externally-provided data to build prompts provided to large language models (LLMs), but the way these prompts are constructed causes the LLM to fail to distinguish between user-supplied inputs and developer provided system directives.
An attacker operating through a network path may attempt exploitation when the stated preconditions are met. If successful, the issue may cause the confidentiality, integrity or availability impact described by the vendor.
A prompt injection vulnerability in the shell tool in Amazon Strands Agents Tools before 0.8.0 might allow remote actors to execute arbitrary operating system commands on the agent's host via a crafted prompt that sets the non_interactive parameter to true, bypassing the human consent gate. To remediate this issue, users should upgrade to version 0.8.0.
The product uses externally-provided data to build prompts provided to large language models (LLMs), but the way these prompts are constructed causes the LLM to fail to distinguish between user-supplied inputs and developer provided system directives.
An attacker operating through a network path may attempt exploitation when the stated preconditions are met. If successful, the issue may cause the confidentiality, integrity or availability impact described by the vendor.
CVSS severity, EPSS forecast probability, public exploit material and CISA-confirmed exploitation are separate signals.
No CISA KEV match was present at the last successful refresh. This means no confirmation from that source, not proof of no exploitation.
No exploit-tagged reference or CISA SSVC proof-of-concept state is currently recorded. Research may still exist outside the structured feeds.
CWE-1427: Improper Neutralization of Input Used for LLM Prompting. The product uses externally-provided data to build prompts provided to large language models (LLMs), but the way these prompts are constructed causes the LLM to fail to distinguish between user-supplied inputs and developer provided system directives.
CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:A/VC:H/VI:H/VA:H/SC:N/SI:N/SA:NCommon Vulnerability Scoring System 4.0: the compact vector below is decoded into plain language.
Operational remediation based on structured source evidence.
Published 3 Aug 2026 · Last source change 4 Aug 2026, 19:31 UTC · CWE-1427 · Improper Neutralization of Input Used for LLM Prompting
Core structured fields are present and their contributing authorities are shown above.
No material field changes have been recorded since change tracking began. Routine source refreshes and cosmetic edits are intentionally excluded.