Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2024-58339 is a high-severity Allocation of Resources Without Limits or Throttling (CWE-770) vulnerability in Llamaindex Llamaindex. Its CVSS base score is 8.7 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Network Denial of Service (T1498); ranked at the 44th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as NLP and Transformers; in the Other ATLAS/OWASP Terms risk domain.
The strongest mitigations our analysis identified map to AC-10 (Concurrent Session Control) and SC-6 (Resource Availability) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2024-58339 is an uncontrolled resource consumption vulnerability (CWE-770) affecting LlamaIndex (run-llama/llama_index) versions up to and including 0.12.2. The issue resides in the VannaPack VannaQueryEngine implementation, specifically within the custom_query() function in llama_index/packs/vanna/base.py. This logic generates SQL statements from user-supplied prompts and executes them via vn.run_sql() without enforcing query execution limits, enabling resource exhaustion.
The vulnerability carries a CVSS v3.1 base score of 7.5 (AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H), indicating high severity due to its potential for denial-of-service. Remote attackers require no privileges or user interaction and can exploit it over the network with low complexity. In downstream deployments where untrusted users provide prompts to the VannaQueryEngine, an attacker can supply crafted prompts that generate expensive or unbounded SQL operations, exhausting CPU or memory resources and causing a denial-of-service condition.
Advisories from sources including VulnCheck, Huntr, and the LlamaIndex GitHub repository detail the vulnerability and its exploitation path. Security practitioners should consult these references—such as https://www.vulncheck.com/advisories/llamaindex-vannaqueryengine-sql-execution-allows-resource-exhaustion and https://huntr.com/bounties/a1d6c30d-fce0-412a-bd22-14e0d4c1fa1f—for guidance on identifying affected deployments and implementing mitigations like input validation or query limits.
This issue is particularly relevant to AI/ML workflows, as LlamaIndex is a framework for building LLM-powered applications, potentially exposing data querying interfaces in production RAG systems to resource exhaustion attacks. No real-world exploitation has been reported in the provided details.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-2397
Vulnerability Data
LlamaIndex (run-llama/llama_index) versions up to and including 0.12.2 contain an uncontrolled resource consumption vulnerability in the VannaPack VannaQueryEngine implementation. The custom_query() logic generates SQL statements from a user-supplied prompt and executes them via vn.run_sql() without enforcing query execution limits In…
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downstream deployments where untrusted users can supply prompts, an attacker can trigger expensive or unbounded SQL operations that exhaust CPU or memory resources, resulting in a denial-of-service condition. The vulnerable execution path occurs in llama_index/packs/vanna/base.py within custom_query().
- CWE(s)
AI Security AnalysisAI
- AI Category
- NLP and Transformers
- Risk Domain
- Other ATLAS/OWASP Terms
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: llamaindex
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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- 5 hardening rules · 3 OS baselines
V15.4.4
Mitigating Controls (NIST 800-53 r5) AI
Directly enforces a hard limit on concurrent sessions, structurally preventing unbounded resource allocation.
Requires explicit allocation of resources by priority or quota, directly stopping unlimited allocation.
Imposes a limit on consecutive invalid attempts, preventing one specific class of unbounded resource consumption.
Reduces impact of resulting DoS events without preventing the underlying lack of allocation limits.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Monitoring capacity and taking action to maintain availability directly reduces unchecked resource allocation.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Baseline comparison of CPU, memory and bandwidth usage helps surface uncontrolled resource allocations before they cause service degradation.
Capacity projections and elasticity measures ensure that allocation requests are bounded and can be throttled, reducing the window in which an attacker can force unbounded resource reservations.
Defining retention periods and deletion schedules for backup copies prevents indefinite accumulation of data on storage media without corresponding resource-management controls.
Architectural redundancy and automatic failover limit the impact of an attacker who forces excessive allocations, because spare capacity can absorb the load until the primary instance recovers.
Documented incident response procedures that include activation of continuity plans and controlled recovery help ensure that resource consumption triggered by an incident is bounded and managed rather than left unbounded.
Mandating tested continuity procedures that preserve or replace resource-limiting controls prevents an attacker from exploiting the absence of throttling mechanisms during an outage.
Hardening callouts derived
Configuration rules from DISA STIG baselines that bear on weaknesses of the type cited by this CVE. Each rule is shown with the relationship its mapping actually records, against the CWE it was authored against. Derived via CVE→CWE over `controls_xwalks` (authoritative rows only; rows rated `none` are excluded).
Oracle Linux 8 (2 rules)
- V-248552 OL 8 must be configured so that all network connections associated with SSH traffic terminate after becoming unresponsive. prevents CWE-770
- V-248553 OL 8 must be configured so that all network connections associated with SSH traffic are terminated after 10 minutes of becoming unresponsive. prevents CWE-770
Oracle Linux 9 (2 rules)
- V-271710 OL 9 must be configured so that all network connections associated with SSH traffic are terminated after 10 minutes of becoming unresponsive. prevents CWE-770
- V-271709 OL 9 must be configured so that all network connections associated with SSH traffic terminate after becoming unresponsive. prevents CWE-770
RHEL 8 (1 rule)
- V-230244 RHEL 8 must be configured so that all network connections associated with SSH traffic terminate after becoming unresponsive. prevents CWE-770