CVE-2026-28002

Executive Summary

CVE-2026-28002 is a blind SQL injection vulnerability in Arraytics Booktics, a booking/event management application, affecting all versions through 1.0.22. The vulnerability results from improper neutralization of special elements used in an SQL command, allowing an authenticated low-privilege attacker to execute arbitrary SQL queries against the backend database. With a CVSS score of 8.5, the vulnerability carries a HIGH severity rating, primarily due to its network exploitability, low attack complexity, and significant confidentiality impact (C:H) with a scope change enabling lateral database access beyond the initial component. At the time of this report, no patch is available, no exploit code has been publicly disclosed, and the EPSS score has not yet been published by FIRST.org.

Targeted organizations include any enterprise or SMB relying on Booktics for event management, ticket booking, or scheduling operations. Successful exploitation could result in wholesale database exfiltration, including personally identifiable information (PII), payment records, credentials, and booking histories. The blind nature of the injection means attackers may extract data row-by-row using boolean-based or time-based techniques, bypassing traditional error-based detection mechanisms.

Technical Analysis

The NVD description identifies CVE-2026-28002 as an "Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection') vulnerability" in Arraytics Booktics, explicitly characterized as enabling Blind SQL Injection. This aligns with CWE-89, the canonical weakness for SQL injection classes.

Vulnerability Mechanism (Class-Level): The root cause is insufficient sanitization or parameterization of user-supplied input that is subsequently concatenated into SQL query strings. Rather than using prepared statements with bound parameters, the application constructs SQL queries by directly interpolating user-controlled data. Because the injection is blind, the application does not return database error messages or query output directly to the client; however, the attacker can infer query results indirectly through differences in application behavior — such as HTTP response times (time-based), page content changes (boolean-based), or conditional error responses.

Attack Surface: Booktics is a web application, and the vulnerable vectors are the HTTP request parameters feeding database queries. Given the low privilege requirement (PR:L), the attacker must possess a valid account with minimal permissions — typical of a standard user or booking attendant role. The attack is performed against network-facing endpoints, requires no user interaction, and does not necessitate special conditions beyond the low-privilege account.

Insufficient Technical Detail: The NVD description does not specify the exact affected module, function names, endpoint paths, or parameter identifiers. Consequently, this analysis is restricted to the generic SQL injection mechanism. It is likely that injection points exist in search filters, booking queries, reporting modules, or administrative dashboards where user-controlled criteria are passed to SQL statements. Specific technical implementation details — including vulnerable function names or URL paths — cannot be verified from the provided data and are not invented here.

Blind SQL Injection Nuance: In blind scenarios, the attacker typically leverages:

• Boolean-based techniques (AND 1=1 vs AND 1=2) comparing response content.
• Time-based techniques (WAITFOR DELAY '0:0:5' on MSSQL or SLEEP(5) on MySQL) measuring response latency.
• Out-of-band (OOB) techniques using DNS or HTTP callbacks if database features permit (e.g., LOAD_FILE on MySQL or xp_dirtree on MSSQL).

The latter is particularly damaging in enterprise environments where egress traffic is not restricted, enabling near-silent data extraction.

Exploitation Scenarios

No public PoC exists for this CVE at the time of writing; the following attack chain is inferred from the vulnerability class (blind SQLi) and the CVSS vector details. This attack chain is representative and may require adjustment upon disclosure of technical specifics.

Step 1 — Reconnaissance & Target Identification The attacker identifies Booktics instances via web fingerprinting (e.g., HTML source indicating the Booktics framework, specific meta tags, or asset paths). Shodan or Google dorking can surface exposed instances. Given PR:L, the attacker registers or obtains a low-privilege account (e.g., standard user) on the target instance.

Step 2 — Vulnerability Trigger The attacker enumerates HTTP request parameters used in search, filtering, or data retrieval functions — e.g., booking search forms, event listing filters, or report queries. The attacker injects a single quote (') into a parameter and observes the application's behavior. A response without an error but with a different response size, status code, or response time indicates a non-parameterized SQL query.

Step 3 — Payload Execution (Class-Level Example) Using boolean-based blind inference, the attacker crafts payloads such as:

• ' AND (SELECT SUBSTRING(version(),1,1))='M — inferring the first character of the database version.
• ' AND (SELECT COUNT(*) FROM information_schema.tables)>10 — enumerating schema volume.

Time-based alternatives:

• ' OR SLEEP(5)-- — if the backend is MySQL, inducing a 5-second delay to confirm injectability and extract data via response timing.

The attacker iteratively extracts data character-by-character or bit-by-bit, using conditional logic to recover database contents.

Step 4 — Post-Exploitation Impact Once the database is enumerated, the attacker extracts credential hashes, personal data, booking records, and payment PII. Depending on the database user's privilege level and the DBMS configuration, the attacker may also:

• Write files to the server filesystem (if FILE privilege exists on MySQL).
• Read sensitive server files via LOAD_FILE().
• Execute OS commands via SQL extensions like xp_cmdshell on MSSQL (if enabled and privileges allow).

The scope-change component (S:C) in the CVSS vector indicates successful exploitation can impact resources beyond the vulnerable component — e.g., other databases on the same server or the underlying operating system.

Impact Assessment

• CVSS Score: 8.5 (High) — Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:N/A:L
• Confidentiality Impact (HIGH): Primary impact is total disclosure of the backend database contents, including user accounts, payment information, booking records, and potentially sensitive organizational data. This is the dominant damage vector.
• Integrity Impact (LOW): Limited integrity damage is possible — the attacker may modify or delete records if the database user has write privileges, though the CVSS vector suggests integrity impact is minimal.
• Availability Impact (LOW): Targeted denial-of-service could be achieved via destructive SQL commands (e.g., DROP TABLE), though this is not the primary exploitation objective.
• Scope Change (S:C): Exploitation can affect resources beyond the initial application — including other applications sharing the same database server or the underlying host OS.
• Attack Complexity (LOW) & Privileges Required (LOW): A valid low-privileged account suffices; no special conditions or user interaction required, making exploitation straightforward once credentialed access is obtained.

Blast Radius: Any organization using Booktics through version 1.0.22 — including event management firms, ticket resellers, educational institutions, and hospitality sectors relying on the platform. The sensitive nature of booking/payment data elevates the regulatory impact (GDPR, PCI-DSS, CCPA), potentially triggering mandatory breach notification obligations.

Business Impact: Direct financial losses from fraud (if payment data is exposed), legal liability, reputational damage, and potential regulatory fines. The lack of a patch means the exposure remains indefinitely.

Detection Guidance

Sigma Rule

title: Blind SQL Injection Attempt Against Arraytics Booktics
id: a3c8d15e-7f2b-4c9a-9e11-d4f0a6b2c8e5
status: experimental
description: Detects patterns indicative of blind SQL injection attempts targeting Booktics application parameters.
author: Valtersit Threat Intelligence
date: 2026/02/15
logsource:
  category: webserver
  product: apache
  service: access
detection:
  selection_boolean:
    c-uri|contains:
      - "' AND"
      - "' OR"
      - "AND SLEEP("
      - "OR SLEEP("
      - "AND BENCHMARK("
      - "IF("
      - "SUBSTRING("
  selection_time:
    c-uri|contains:
      - "WAITFOR"
      - "DELAY '0:0:"
      - "pg_sleep("
      - "SLEEP("
  selection_error:
    c-uri|contains:
      - "information_schema.tables"
      - "SELECT COUNT(*)"
      - "UNION SELECT"
  condition: selection_boolean or selection_time or selection_error
  timeframe: 5m
level: high
falsepositives:
  - Legitimate developer traffic using SQL keywords in API parameters (rare)
  - Fuzzing tools used by development teams
fields:
  - c-uri
  - c-remote-ip
  - sc-status

YARA Rule

rule Booktics_Blind_SQLi_Attempt
{
    meta:
        author = "Valtersit Threat Intelligence"
        description = "Detects payloads characteristic of blind SQL injection attempts against Arraytics Booktics"
        cve = "CVE-2026-28002"
        date = "2026-02-15"
        severity = "high"
    strings:
        $s1 = "AND SLEEP(" ascii wide nocase
        $s2 = "OR SLEEP(" ascii wide nocase
        $s3 = "SELECT SUBSTRING(" ascii wide nocase
        $s4 = "information_schema.tables" ascii wide nocase
        $s5 = "WAITFOR DELAY" ascii wide nocase
        $s6 = "pg_sleep(" ascii wide nocase
        $s7 = "BENCHMARK(" ascii wide nocase
        $s8 = "' AND '1'='1" ascii wide nocase
        $s9 = "' OR '1'='1" ascii wide nocase
        $s10 = "IF(" ascii wide nocase
    condition:
        (uint16(0) == 0x4D5A or uint16(0) == 0x7F45) or
        (1 of them) or (2 of them in any order within 500 bytes)
}

Suricata IDS Rule

alert http any any -> $HOME_NET any (msg:"ET WEB_SPECIFIC_APPS Arraytics Booktics Blind SQL Injection Attempt (CVE-2026-28002)"; flow:to_server,established; content:"GET"; http_method; content:"%27"; http_uri; content:"AND"; http_uri; nocase; content:"SLEEP"; http_uri; nocase; within:100; reference:cve,2026-28002; classtype:web-application-attack; sid:28100001; rev:1;)

Note: Additional variants covering POST bodies and other parameters:

alert http any any -> $HOME_NET any (msg:"ET WEB_SPECIFIC_APPS Booktics SQLi - Boolean Response Pattern (CVE-2026-28002)"; flow:to_server,established; content:"AND"; nocase; http_client_body; content:"1=1"; nocase; http_client_body; http_uri; reference:cve,2026-28002; classtype:web-application-attack; sid:28100002; rev:1;)

Elastic Detection

eql:
  query: |
    sequence by source.ip with maxspan=30s
      [network where dns.question.name != null and
        process.name != null]  // OOB based exfiltration
      [http where http.request.body.text like~ "*AND*SLEEP*" or
        http.request.body.text like~ "*OR*SLEEP*" or
        http.request.body.text like~ "*information_schema*"]
      [http where http.request.body.text like~ "*1=1*" or
        http.request.body.text like~ "*1=2*"]
  filter:
    - term: http.request.method -> "POST"
    - term: http.response.status_code -> "200"

Splunk SPL Query

index=web sourcetype=access_combined
  (uri_path=* OR form_data=*)
  AND (
    (form_data LIKE "*%27%20AND%20*" OR form_data LIKE "*' AND *") OR
    (form_data LIKE "*SLEEP(*") OR
    (form_data LIKE "*BENCHMARK(*") OR
    (form_data LIKE "*information_schema*") OR
    (form_data LIKE "*WAITFOR%20DELAY*") OR
    (form_data LIKE "*pg_sleep(*")
  )
  | stats count by clientip, uri_path, method, _time
  | where count > 3
  | table _time, clientip, uri_path, method, count

Additional SPL with response timing threshold (time-based detection):

index=web sourcetype=access_combined
  | eval req_time_seconds = (req_time_ms/1000)
  | where req_time_seconds > 5
  | stats count avg(req_time_seconds) as avg_time by clientip, uri_path
  | where count > 5

Wazuh OSSEC Rule

<group name="web,sql_injection,">
  <rule id="281002" level="14">
    <decoded_as>json</decoded_as>
    <field name="url">\.(php|asp|aspx).*</field>
    <regex>(\'(AND|OR)\s*(SLEEP|BENCHMARK|SUBSTRING|IF)\()|(information_schema)|(WAITFOR\s+DELAY)|(pg_sleep)</regex>
    <description>Possible blind SQL injection attempt targeting Booktics (CVE-2026-28002)</description>
    <group>web_application_attack,sql_injection,</group>
    <mitre>
      <id>T1190</id>
    </mitre>
  </rule>

  <rule id="281003" level="10">
    <decoded_as>json</decoded_as>
    <field name="url">\.(php|asp|aspx).*</field>
    <regex>%27\s*(AND|OR)\s*%27?[0-9]%27?[=]\s*%27?[0-9]</regex>
    <description>Booktics blind SQLi boolean-based attempt (CVE-2026-28002)</description>
    <group>web_application_attack,sql_injection,</group>
    <mitre>
      <id>T1190</id>
    </mitre>
  </rule>
</group>

Mitigation & Patch Guidance

Patch Confidence: 0/4 — UNPATCHED. No evidence of a vendor fix exists from any tracked source. The vendor (Arraytics) has not released a patched version as of this report.

Immediate Mitigations (compensating controls):

1. Web Application Firewall (WAF) — Deploy OWASP ModSecurity Core Rule Set (CRS) with SQL injection rules enabled to filter malicious payloads at the perimeter.
2. Network Segmentation — Restrict database access to application servers only; ensure the DBMS is not exposed to the internet.
3. Database User Privileges — Review and limit the database account used by Booktics to least-privilege; remove FILE, SUPER, and administrative privileges.
4. Outbound Egress Filtering — Block outbound DNS and HTTP/HTTPS traffic from database servers to prevent out-of-band (OOB) data exfiltration channels.
5. Disable Unused Features — If certain Booktics modules are not required (e.g., reporting, advanced search), disable them to reduce the attack surface.
6. Monitor Authenticated Sessions — Tighten account creation policies; validate user registration to reduce PR:L attack surface availability.

Patch/Upgrade Steps:

• Immediately contact Arraytics support to request a patched release; demand a public timeline. Monitor vendor channels for security advisories.
• If a patch becomes available, apply in a staging environment first, then roll out to production. Verify no functionality regression.
• Until patched, completely isolate Booktics instances from the internal network if they do not require external access.

Long-Term Hardening:

1. Code Audit — Commission a security audit of the application codebase, prioritizing SQL query construction; enforce parameterized queries/prepared statements.
2. Input Validation — Implement rigorous application-level allowlist validation for all user-supplied inputs.
3. Vendor Accountability — If the product is unmaintained, evaluate migration to an actively maintained alternative booking platform.
4. Credential Hygiene — Rotate all database credentials and application secrets used by Booktics.
5. Incident Preparedness — Prepare incident response playbooks for data exfiltration scenarios; ensure backups are isolated and immutable.

References

1. NVD Entry — https://nvd.nist.gov/vuln/detail/CVE-2026-28002
2. CWE-89 — https://cwe.mitre.org/data/definitions/89.html (SQL Injection weakness class)
3. CISA KEV — Not listed; no known exploit-in-the-wild evidence at time of writing.
4. MITRE ATT&CK Technique T1190 — https://attack.mitre.org/techniques/T1190/ (Exploit Public-Facing Application)
5. OWASP SQL Injection Prevention Cheat Sheet — https://cheatsheetseries.owasp.org/cheatsheets/SQL_Injection_Prevention_Cheat_Sheet.html

Known Threat Actor Campaigns: None identified as of this report. No exploit code, PoC, or in-the-wild exploitation evidence has been published within tracked sources. The lack of a patch and the low complexity of exploitation make this a likely candidate for inclusion in future exploit toolkits; organizations should treat this as a high-priority risk despite the absence of active campaigns.