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Sef Chatbot Platform EUVDEUVD-2026-91329

| CVE-2026-80298 HIGH
SQL Injection (CWE-89)
2026-10-02 TR-CERT GHSA-4fxr-7rqw-6ppg
8.8
CVSS 3.1 · Vendor: TR-CERT
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Attack ChainAIDerived

Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain

  1. Access
    Obtain low-privilege account access
  2. Delivery
    Submit crafted SQL payload in input field
  3. Exploit
    Bypass input neutralization (CWE-89)
  4. Execution
    Execute injected query on backend database
  5. Impact
    Exfiltrate or tamper with stored data

Vulnerability Assessment

Weakness
CWE
OWASP Top 10:2025
A05:2025 - Injection
ASVS 5.0
V1 - Encoding and Sanitization Parameterized queries, prepared statements
MITRE ATT&CK

2 techniques across 2 tactics: Initial Access, Persistence

The technique list with ATT&CK links and the kill-chain view is part of the Basic plan and up.

Exploitation Conditions

Exploitation requires a valid low-privilege authenticated session on the Sef - AI Chatbot Platform (CVSS PR:L), after which an attacker sends crafted SQL metacharacters through a user-controllable input that reaches a database query without proper neutralization (CWE-89). No user interaction is needed (UI:N) and the attack is network-reachable (AV:N) with low complexity (AC:L). The principal limiting factor is the authentication requirement - an attacker must first possess or acquire platform credentials - and the narrow deployment base of this specific vendor product; the exact vulnerable endpoint/parameter is not disclosed in the available data, and all affected instances must be running a version prior to 2.1.

Impact

This is a credible, actionable priority rather than a high-CVSS-but-low-risk issue, though the real-world exposure is bounded by product footprint. The CVSS 3.1 vector (AV:N/AC:L/PR:L/UI:N) describes a network-reachable, low-complexity SQL injection requiring only low-level authenticated privileges and no user interaction, with full C:H/I:H/A:H impact - consistent with a classic CWE-89 flaw where an authenticated user can read, modify, or destroy backend database contents. The signals are largely one-directional: the CVSS is high and the attack is easy once a foothold exists. However, several key risk signals are MISSING from the input and must not be assumed present: there is no EPSS score, no CISA KEV listing, and no indication of public POC/exploit code, so there is no evidence of active or widespread exploitation. The report originates from TR-CERT (Turkey's national CERT), which confirms the flaw's existence but does not itself imply in-the-wild use. Net: treat as a genuine high-severity vulnerability warranting prompt patching to version 2.1 for any organization running this platform, but the absence of EPSS/KEV/POC data means the likelihood of opportunistic mass exploitation is unquantified and currently appears lower than the severity alone would suggest.

Exploit ScenarioDerived

An attacker who holds or obtains low-privilege authenticated access to the Sef - AI Chatbot Platform (e.g., a standard application account) submits crafted input containing SQL metacharacters into a vulnerable parameter. Because special elements are not neutralized (CWE-89), the injected SQL executes against the backend database, letting the attacker exfiltrate or alter stored data. No public exploit code has been identified at time of analysis, and no user interaction is required.

This Week Schedule remediation this week. Why: HIGH severity (CVSS 7.0-8.9).
Patch available 0.4% exploitation probability (EPSS)

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AnalysisAIv1 – Oct 02, 2026

SQL injection in HAVELSAN's Sef - AI Chatbot Platform, affecting all releases prior to 2.1, lets an attacker who holds a valid low-privilege account feed crafted SQL metacharacters through a user-controllable input that is concatenated into a database query, yielding high confidentiality, integrity, and availability impact (CVSS 8.8, CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H). The issue is network-reachable with low attack complexity and needs no user interaction, but the vector's PR:L means an attacker must first obtain platform credentials; no public exploit code and no confirmed active exploitation were identified at time of analysis, and the TR-CERT advisory (https://siberguvenlik.gov.tr/guvenlik-bildirimleri/detay/tr-26-1241) does not disclose the specific vulnerable endpoint or parameter. This is a credible, actionable priority rather than a high-CVSS-but-low-risk issue, though real-world exposure is bounded by the narrow deployment base of this specific vendor product.

RemediationAI

The primary fix is to upgrade Sef - AI Chatbot Platform to version 2.1 or later, which the TR-CERT advisory identifies as the first release outside the affected 'before 2.1' range; confirm the deployed build after upgrading rather than assuming a package refresh completed, and check the advisory at https://siberguvenlik.gov.tr/guvenlik-bildirimleri/detay/tr-26-1241 for any vendor-supplied specifics. If the upgrade cannot be staged immediately, use compensating controls that address the PR:L prerequisite and the SQL sink: tighten account issuance and revoke or disable dormant and over-privileged chatbot accounts (effective but disruptive to active users), and run the platform against a least-privilege database account with no DDL, file, or cross-schema rights so an injection cannot be escalated to server-level commands (requires a controlled config change and retesting of application queries). Restrict network access to the platform's authenticated interfaces to trusted management networks or VPN rather than the open internet (reduces reachable surface but breaks external or remote users), and deploy a WAF with tuned SQL-injection rules in front of it as a detection-and-delay layer, accepting that SQLi ruleset bypasses are common, that false positives can break chat traffic, and that a WAF is not a substitute for the code-level fix. Because the vulnerable endpoint and parameter are undisclosed, do not rely on blocking a single known path; instead enable verbose database and application logging, alert on SQL error strings and anomalous query volumes, and rotate the platform's database credentials after any suspected compromise. Development teams should remediate at source by replacing dynamic SQL string concatenation with parameterized statements or stored procedures for every query that consumes chatbot or operator input.

Affected VersionsENISA

Sef - AI Chatbot Platform 0 <2.1

Affected Packages

euvd sef_ai_chatbot_platform fix: 2.1

Source: OSV (Open Source Vulnerabilities)

Affects your stack

Affects 1 package in euvd

Checking this CVE against your own stacks and servers is part of the Basic plan and up.

Technical ContextAI · show details

The root cause is CWE-89, improper neutralization of special elements used in an SQL command: user-supplied input is incorporated into a SQL statement without parameterization or adequate escaping, so an attacker can alter query structure to read, modify, or destroy data or otherwise manipulate the backend database. In an AI chatbot platform such as Sef, the risky surface typically includes conversation/session handlers, knowledge-base or FAQ lookups, message-history retrieval, feedback or logging endpoints, and any administrative search function where chatbot or operator text is turned into dynamic SQL. The CPE entry cpe:2.3:a:havelsan_inc.:sef_-_ai_chatbot_platform:*:*:*:*:*:*:*:* uses a wildcard version, indicating that the advisory did not enumerate individual builds and that every release before 2.1 should be treated as affected. The assessed vector AV:N/AC:L/PR:L/UI:N/S:U means the query can be reached over the network by any authenticated low-privilege user with no victim interaction, and because the scope is unchanged (S:U) the impact is confined to the platform and its database rather than spreading to other security authorities, while C:H/I:H/A:H reflects that a successful injection can fully compromise data confidentiality and integrity. The exact database engine, vulnerable parameter, and required privilege level within the application are not confirmed by the available data, so the injection may be equally reachable from an ordinary chat user or a more privileged console user.

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Severity by source

Vendor (TR-CERT) PRIMARY 8.8 HIGH
AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
vuln.today AI 8.8 HIGH

Network-reachable SQL injection needing a low-privilege account (PR:L) but no interaction; low complexity and full database read/write/destroy yield C:H/I:H/A:H.

3.1 AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
4.0 AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N

Primary rating from Vendor (TR-CERT).

CVSS VectorVendor: TR-CERT

Attack Vector
Network
Attack Complexity
Low
Privileges Required
Low
User Interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High

Lifecycle Timeline

2
Patch available
Oct 02, 2026 - 10:01 EUVD
CVE Published
Oct 02, 2026 - 09:07 cve.org
HIGH 8.8

DescriptionCVE.org

Improper neutralization of special elements used in an SQL command ('SQL injection') vulnerability in HAVELSAN Inc. Sef - AI Chatbot Platform allows SQL Injection.

This issue affects Sef - AI Chatbot Platform: before 2.1.

Executive ViewAI

Why It Matters

HAVELSAN's Sef AI Chatbot Platform, in every release prior to 2.1, carries a SQL injection flaw that an authenticated low-privilege user can reach over the network with no user interaction, exposing the confidentiality, integrity, and availability of the database the chatbot queries. With no vendor patch available, any organization running Sef in a customer-facing or internal service role holds unresolved exposure to whatever data that chatbot account can reach, and credentials rather than network position are the only barrier. Deployment of this specific product is narrow, which limits the blast radius across the industry, but for affected organizations this is a confirmed high-severity defect requiring near-term containment rather than a theoretical concern.

Business Impact: High
Compensating Controls

No vendor-released patch identified at time of analysis. Interim mitigations: enforce strict least privilege on the Sef database account, restrict and re-validate all low-privilege accounts, deploy WAF/reverse-proxy virtual patching for SQL injection on chatbot input paths, network-segment the Sef database from other systems, enable database activity monitoring and SQL anomaly alerting, and consider isolating or disabling the affected chatbot function until a fix is confirmed.

Threat Intelligence Overview

EPSS Score
0.4%
Top 65% exploitable
Prevalence
Low
niche vendor-specific AI chatbot platform from a Turkish defense/tech firm
Data Quality
4 sources
Confidence: Medium

How this decision was reached

The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.

SignalValue
Severity HIGH
CISA KEV No
Public POC No
EPSS 0.4%
Patch available Yes
Active threat No
Deciding rule
HIGH severity (CVSS 7.0-8.9)
What every action level means
Emergency Immediate action required. Criteria: CRITICAL + in CISA KEV (actively exploited) without patch, OR CRITICAL + EPSS > 30% without patch, OR CRITICAL + active threat signals without patch.
Act Now Prioritize within 24-48h. Criteria: in KEV with patch available, OR CRITICAL + public POC, OR HIGH + EPSS > 10%, OR CRITICAL + active threat, OR any CRITICAL severity.
This Week Schedule remediation this week. Criteria: HIGH severity (CVSS 7.0-8.9). Patch within normal change window.
This Month Plan within 30 days. Criteria: MEDIUM severity (CVSS 4.0-6.9), lower exploitation probability. Include in regular patch cycle.
Monitor Track and reassess. Criteria: LOW severity (CVSS 0.1-3.9), minimal exploitation risk. No immediate action needed.

SSVC AssessmentENISA

SSVC Decision
Scheduled
Exploitation
None
System Exposure· derived
Open
Automatable
No
Human Impact
High
Technical Impact
Total

Priority Score

44
Low Medium High Critical
KEV: 0
EPSS: 0
CVSS: +44
PoC: 0
Weaponized: 0
Threat intel: 0
Gov advisory: 0

Attack Technique

SQL injection exploits the way applications construct database queries by mixing user input directly into SQL statements.

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