CVE-2025-57806VulnerabilityPublished 3 Sep 2025

CVE-2025-57806: LearningCircuit local-deep-research · Cleartext Storage of Sensitive Information

Affects LearningCircuit local-deep-researchSource CVE Database V5

Not known to be exploited · CVSS 6.9 Medium · fixed in 1.0.0 : update LearningCircuit local-deep-research when convenient.

Data as of 25 Oct 2026, 19:02 UTC

CVSS 4.0 base score

6.9Medium

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

EPSS: 0.07% chance of exploitation in 30 days – higher than 0% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch: Available – fixed in 1.0.0

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

Attack Vector: Local
Attack Complexity: Low
Attack Requirements: None
Privileges Required: None
User Interaction: None
Vulnerable system confidentiality: High
Vulnerable system integrity: None
Vulnerable system availability: None
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: Local: The vulnerable system is not bound to the network stack and the attacker’s path is via read/write/execute capabilities. Either the attacker exploits the vulnerability by accessing the target system locally (e.g., keyboard, console), or through terminal emulation (e.g., SSH); or the attacker relies on User Interaction by another person to perform actions required to exploit the vulnerability (e.g., using social engineering techniques to trick a legitimate user into opening a malicious document).
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: None: The attacker is unauthorized prior to attack, and therefore does not require any access to settings or files of the vulnerable system to carry out an attack.
User Interaction: None: The vulnerable system can be exploited without interaction from any human user, other than the attacker.
Vulnerable system confidentiality: High: There is a total loss of confidentiality, resulting in all information within the Vulnerable System being divulged to the attacker. Alternatively, access to only some restricted information is obtained, but the disclosed information presents a direct, serious impact. For example, an attacker steals the administrator's password, or private encryption keys of a web server.
Vulnerable system integrity: None: There is no loss of integrity within the Vulnerable System.
Vulnerable system availability: None: There is no impact to availability within 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 3 Sep 2025
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 2026-10-25.

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

AI-suggested

European organizations should immediately upgrade local-deep-research to version 1.0.0 or later, where the vulnerability has been fixed. Until upgrade is possible, organizations should restrict access to the host filesystem and container environments to trusted personnel only, implementing strict access controls and monitoring for unauthorized access attempts. Encrypting the underlying storage volume or filesystem where the SQLite database resides can provide an additional layer of protection. Organizations should also consider isolating the application within hardened containers with minimal privileges and use host-based intrusion detection systems to alert on suspicious file access. Reviewing and rotating any API keys stored in affected versions is critical to prevent misuse. Additionally, organizations should request or implement configuration options to allow relocation of the database file to more secure locations and advocate for encryption of sensitive data at rest in future software versions. Finally, conducting regular audits of container and host security posture will help detect potential exposures early.

Description

Local Deep Research is an AI-powered research assistant for deep, iterative research. Versions 0.2.0 through 0.6.7 stored confidential information, including API keys, in a local SQLite database without encryption. This behavior was not clearly documented outside of the database architecture page. Users were not given the ability to configure the database location, allowing anyone with access to the container or host filesystem to retrieve sensitive data in plaintext by accessing the .db file. This is fixed in version 1.0.0.

Impact

For European organizations using local-deep-research versions prior to 1.0.0, this vulnerability poses a significant risk to the confidentiality of sensitive information, particularly API keys that could grant unauthorized access to external services or internal resources. Since the vulnerability requires local or container-level access, the primary threat vector is insider threats or attackers who have already compromised the host environment. The exposure of API keys can lead to further lateral movement, data exfiltration, or abuse of cloud services, potentially resulting in financial loss, reputational damage, and regulatory non-compliance under GDPR due to inadequate protection of sensitive data. Organizations relying on this tool for research involving confidential or proprietary data may face increased risk of intellectual property theft or leakage. The lack of encryption and fixed database location exacerbates the risk, as attackers do not need to bypass additional security controls to retrieve sensitive data. However, the absence of remote exploitability limits the threat to environments where attackers have already gained some level of access.

CWE-312Cleartext Storage of Sensitive Information (opens in a new tab)
Base weaknessOWASP Top 10 A06:2025: Insecure Design (opens in a new tab)
The product stores sensitive information in cleartext within a resource that might be accessible to another control sphere.
Implementation · System Configuration · Operation
When storing data in the cloud (e.g., S3 buckets, Azure blobs, Google Cloud Storage, etc.), use the provider's controls to encrypt the data at rest.
Implementation · System Configuration · Operation
In some systems/environments such as cloud, the use of "double encryption" (at both the software and hardware layer) might be required, and the developer might be solely responsible for both layers, instead of shared responsibility with the administrator of the broader system/environment.
OWASP Cheat Sheets
Secure Design Principles (opens in a new tab)
OWASP ASVS 4.0.3
V8.1.6 (opens in a new tab)
V8.2.3 (opens in a new tab)
V8.2.2 (opens in a new tab)
Attack patterns
Retrieve Embedded Sensitive Data (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).
CWE-522Insufficiently Protected Credentials (opens in a new tab)
Class weaknessOWASP Top 10 A06:2025: Insecure Design (opens in a new tab)
The product transmits or stores authentication credentials, but it uses an insecure method that is susceptible to unauthorized interception and/or retrieval.
Architecture and Design
Use an appropriate security mechanism to protect the credentials.
Architecture and Design
Make appropriate use of cryptography to protect the credentials.
Implementation
Use industry standards to protect the credentials (e.g. LDAP, keystore, etc.).
OWASP Cheat Sheets
Secure Design Principles (opens in a new tab)
OWASP ASVS 4.0.3
V2.10.3 (opens in a new tab)
V2.8.5 (opens in a new tab)
V2.8.4 (opens in a new tab)
Attack patterns
Session Sidejacking (opens in a new tab)
Signature Spoofing by Key Theft (opens in a new tab)
Password Recovery Exploitation (opens in a new tab)
Kerberoasting (opens in a new tab)
Modify Existing Service (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).

References

Community reviews

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Exploitation evidence

What to do

Description

AI analysisMachine-generated, updated 10 Sep 2025, 04:50 UTC

WeaknessesCWE-312, CWE-522

Technical details

References

Community reviews

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