CVE-2026-2532VulnerabilityPublished 16 Feb 2026Updated 23 Feb 2026

CVE-2026-2532: lintsinghua DeepAudit · Server-Side Request Forgery

Affects lintsinghua DeepAuditSource CVE Database V5

Not known to be exploited · CVSS 5.3 Medium.

Data as of 26 Oct 2026, 07:57 UTC

CVSS 4.0 base score

5.3Medium

How severe the flaw is on the 0–10 CVSS scale.

EPSS: 0.2% chance of exploitation in 30 days – higher than 20% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.

CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:X

Attack Vector: Network
Attack Complexity: Low
Attack Requirements: None
Privileges Required: Low
User Interaction: None
Vulnerable system confidentiality: Low
Vulnerable system integrity: Low
Vulnerable system availability: Low
Subsequent system confidentiality: None
Subsequent system integrity: None
Subsequent system availability: None

Bold values are the worst case: easiest to exploit or largest impact.

Attack Vector: Network: The vulnerable system is bound to the network stack and the set of possible attackers extends beyond the other options listed below, up to and including the entire Internet. Such a vulnerability is often termed “remotely exploitable” and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).
Attack Complexity: Low: The attacker must take no measurable action to exploit the vulnerability. The attack requires no target-specific circumvention to exploit the vulnerability. An attacker can expect repeatable success against the vulnerable system.
Attack Requirements: None: The successful attack does not depend on the deployment and execution conditions of the vulnerable system. The attacker can expect to be able to reach the vulnerability and execute the exploit under all or most instances of the vulnerability.
Privileges Required: Low: The attacker requires privileges that provide basic capabilities that are typically limited to settings and resources owned by a single low-privileged user. Alternatively, an attacker with Low privileges has the ability to access only non-sensitive resources.
User Interaction: None: The vulnerable system can be exploited without interaction from any human user, other than the attacker.
Vulnerable system confidentiality: Low: There is some loss of confidentiality. Access to some restricted information is obtained, but the attacker does not have control over what information is obtained, or the amount or kind of loss is limited. The information disclosure does not cause a direct, serious loss to the Vulnerable System.
Vulnerable system integrity: Low: Modification of data is possible, but the attacker does not have control over the consequence of a modification, or the amount of modification is limited. The data modification does not have a direct, serious impact to the Vulnerable System.
Vulnerable system availability: Low: Performance is reduced or there are interruptions in resource availability. Even if repeated exploitation of the vulnerability is possible, the attacker does not have the ability to completely deny service to legitimate users. The resources in the Vulnerable System are either partially available all of the time, or fully available only some of the time, but overall there is no direct, serious consequence to the Vulnerable System.
Subsequent system confidentiality: None: There is no loss of confidentiality within the Subsequent System or all confidentiality impact is constrained to the Vulnerable System.
Subsequent system integrity: None: There is no loss of integrity within the Subsequent System or all integrity impact is constrained to the Vulnerable System.
Subsequent system availability: None: There is no impact to availability within the Subsequent System or all availability impact is constrained to the Vulnerable System.

Definitions: FIRST CVSS v4.0 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 16 Feb 2026
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 2026-10-26.

Disclosed: The CVE record is public on cve.org. Its publication is t = 0.
Detectable: A public nuclei template can find exposed instances, for defenders and attackers alike.
Weaponised: Public exploit code exists in Metasploit or Exploit-DB, or CISA SSVC reports a public proof of concept.
Exploited in the wild: CISA KEV lists it, CISA SSVC rates exploitation active, or a source reports attacks.
Observed by OffSeq Mirage: OffSeq Mirage honeypot sensors recorded attack traffic for this CVE, or found exposed hosts without attack traffic.

Moments are spaced evenly, not to scale; a dashed line marks a gap of six months or more. Deltas count from t = 0. Sources that give only a date (CISA KEV, Exploit-DB, or a time of exactly 00:00Z) read “same day” rather than hours. Metasploit modules carry the flaw’s disclosure date, not their release date, and nuclei templates carry no date, so both appear above but not on the timeline.

What to do

Affected software

Product	Affected	Fixed in
lintsinghuaDeepAudit	Affected =3.0.0 =3.0.1 =3.0.2 =3.0.3	Fixed in–

AI-suggested

Organizations should promptly upgrade lintsinghua DeepAudit to version 3.0.4 or 3.1.0, which contain the official patch for CVE-2026-2532. Until upgrades are applied, network-level mitigations can reduce risk by restricting DeepAudit server outbound HTTP requests to only trusted destinations via firewall rules or proxy filtering. Implement strict egress filtering to prevent unauthorized internal resource access. Additionally, monitor DeepAudit server logs for unusual outbound request patterns indicative of SSRF exploitation attempts. Employ network segmentation to isolate DeepAudit servers from sensitive internal services and metadata endpoints. Review and harden any API or service endpoints accessible by DeepAudit to limit exposure. Finally, maintain up-to-date vulnerability management and incident response plans to quickly address any emerging threats related to this vulnerability.

Description

A vulnerability was detected in lintsinghua DeepAudit up to 3.0.3. This issue affects some unknown processing of the file backend/app/api/v1/endpoints/embedding_config.py of the component IP Address Handler. Performing a manipulation results in server-side request forgery. It is possible to initiate the attack remotely. Upgrading to version 3.0.4 and 3.1.0 is capable of addressing this issue. The patch is named da853fdd8cbe9d42053b45d83f25708ba29b8b27. It is suggested to upgrade the affected component.

Impact

The SSRF vulnerability in DeepAudit can allow attackers to coerce the vulnerable server into making arbitrary HTTP requests to internal or external systems. This can lead to unauthorized access to internal services, potentially exposing sensitive information such as internal APIs, metadata services, or administrative interfaces. Organizations relying on DeepAudit for security auditing may face risks of data leakage, internal reconnaissance, or further compromise if attackers leverage SSRF to chain additional exploits. The impact is particularly significant in environments where DeepAudit servers have network access to sensitive internal resources or cloud metadata endpoints. Although the vulnerability has medium severity, the ease of remote exploitation without authentication increases risk. Exploitation could disrupt auditing operations or compromise the confidentiality and integrity of internal systems. However, no known active exploitation has been reported, somewhat limiting immediate risk. Nonetheless, the potential for lateral movement and internal network exposure makes timely remediation critical.

References

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Exploitation evidence

What to do

Affected software

Description

AI analysisMachine-generated, updated 23 Feb 2026, 21:17 UTC

Technical details

References

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