Solutions/Email Scam Detector

Email Scam Image Detection

Phishing emails now weaponize AI-generated headshots, forged letterheads, and fabricated documents to bypass human judgment. Sightova intercepts the visual layer of email fraud before it reaches your team.

API: v2.EMAIL_SCAN
BRANDS: 50K+ INDEXED
COMPLIANCE: SOC2

Scanning Capabilities

QUERY: SELECT * FROM email_defense_modules
ESD-HEAD-01
SCAN MODULE

Synthetic Headshot Detection

Identify AI-generated profile photos used to fabricate fake identities in business email compromise attacks. Our models detect the subtle pupil geometry and hair rendering flaws unique to portrait generators.

PORTRAIT ANALYSISPUPIL GEOMETRYGAN DETECTIONIDENTITY VERIFICATION
ESD-LTRHD-02
SCAN MODULE

Fake Letterhead Analysis

Decompose document headers to verify corporate letterheads against known templates. Detect pixel-level inconsistencies in logos, fonts, and layout spacing that indicate fabricated correspondence.

TEMPLATE MATCHINGFONT FORENSICSLAYOUT ANALYSISHEADER VERIFICATION
ESD-QR-03
SCAN MODULE

QR Code Verification

Decode and inspect embedded QR codes before they reach end users. Flag codes that redirect to credential-harvesting domains, track suspicious URL shorteners, and identify steganographic payloads.

URL INSPECTIONDOMAIN ANALYSISPAYLOAD DETECTIONREDIRECT TRACING
ESD-LOGO-04
SCAN MODULE

Logo Tampering Detection

Compare embedded brand marks against a living database of verified corporate assets. Detect color shifts, aspect ratio distortions, and AI-regenerated versions designed to bypass simple hash checks.

BRAND DATABASECOLOR ANALYSISRATIO VERIFICATIONPERCEPTUAL HASHING
ESD-DOC-05
SCAN MODULE

Document Forgery Scanning

Analyze attached PDFs and images of invoices, contracts, or compliance documents for signs of digital splicing, text overlay injection, and metadata inconsistencies that reveal post-creation editing.

SPLICE DETECTIONTEXT OVERLAYMETADATA AUDITCOMPRESSION ANALYSIS
ESD-BRAND-06
SCAN MODULE

Brand Impersonation Shield

Continuously monitor visual assets across email streams for unauthorized use of your brand identity. Receive real-time alerts when attackers deploy look-alike logos or spoofed marketing materials.

BRAND MONITORINGLOOK-ALIKE DETECTIONREAL-TIME ALERTSVISUAL FINGERPRINT
// ATTACHMENT-FORENSICS

Visual Threat Intelligence for Email

Traditional email security filters text, domains, and sender reputation — but modern phishing attacks have shifted to the visual layer. AI-generated headshots pass DMARC checks. Forged invoices evade keyword filters. Sightova closes the gap by treating every image attachment as a potential threat vector.

  • Inline scanning of all image MIME attachments
  • Cross-reference against 50K+ verified brand asset databases
  • Webhook alerts with threat classification and evidence payloads
RESPONSE /EMAIL_SCAN_V2
{
  "scan_id": "es-7f2a91bc",
  "threat_level": "HIGH",
  "attachments_scanned": 3,
  "findings": [
    {
      "file": "cfo_portrait.jpg",
      "type": "SYNTHETIC_HEADSHOT",
      "generator": "ThisPersonDoesNotExist",
      "confidence": 0.996
    },
    {
      "file": "invoice_q4.pdf",
      "type": "FORGED_LETTERHEAD",
      "brand_match": "Acme Corp (87% similar)"
    }
  ],
  "action": "QUARANTINE"
}

The Visual Side of Email Fraud: What Text Filters Will Never Catch

Email remains the primary attack vector for cybercriminals, but the nature of phishing has fundamentally changed. Modern business email compromise campaigns no longer rely solely on spoofed domains and urgent language. Attackers now embed AI generated headshots to fabricate convincing sender identities, forge corporate letterheads pixel by pixel, and attach manipulated invoices that pass cursory human review. Organizations that rely exclusively on DMARC, SPF, and keyword scanning are missing an entire threat surface, one that a purpose built ai image detector is uniquely positioned to close.

Fake Faces, Forged Logos, and the New Phishing Playbook

The most effective phishing emails in 2025 look nothing like the "Nigerian prince" spam of a decade ago. They arrive with a photorealistic AI generated headshot of a fictional CFO, a pixel perfect company letterhead, and an attached invoice that matches the target organization's actual vendor formatting. Every visual element is specifically designed to exploit the trust gap that text filters leave wide open.

Generative AI already enables attackers to produce headshots that pass reverse image searches, create branded PDF attachments with perfect font matching, and synthesize voice messages that complement the visual deception. The same open source model proliferation fueling deepfake generation is also powering a new generation of phishing toolkits that package sender photo, letterhead, invoice, and follow up voice note into a single automated pipeline.

$2.7 Billion Lost, and Climbing

The FBI reports that business email compromise caused over $2.7 billion in losses in a single year, and that figure continues to climb as AI lowers the barrier to entry for sophisticated fraud. Industries with complex supply chains, frequent vendor payments, and distributed workforces are especially vulnerable. By 2030, researchers predict that AI generated phishing content will outpace manually crafted attacks by a factor of ten.

Phishing Kits Will Soon Write Themselves

The next generation of attack toolkits will offer fully automated email package creation, tailored to a specific target using scraped LinkedIn data and corporate filings. One text prompt will generate the sender persona, the letterhead, the invoice, and even the follow up correspondence. Defending against this shift requires the same multi layered approach that modern cybersecurity AI detection platforms bring to network security, applied specifically to the visual layer of email communication.

The target is not just large enterprises. Small and midsize businesses with lean finance teams and limited security infrastructure are increasingly in the crosshairs. A single successful BEC attack can represent months of revenue for a 50 person company, making the return on investment for attackers exceptionally high.

Scanning Every Pixel Before It Reaches the Inbox

Sightova intercepts every image attachment and embedded visual element before it reaches the recipient. Synthetic headshots are flagged by analyzing pupil geometry, hair rendering patterns, and GAN specific artifacts that portrait generators consistently produce. Letterheads and logos are decomposed and compared against a living database of over 50,000 verified corporate brand assets, catching color shifts, aspect ratio distortions, and AI regenerated variants designed to bypass simple hash checks.

Attached documents undergo metadata verification and compression forensics to detect editing that occurred after the original creation. Every flagged attachment includes a structured evidence payload with generator identification, brand match scores, and forensic annotations that your security operations team can use to triage, escalate, or automate quarantine decisions.

Closing the Gap in Your Email Security Stack

Sightova integrates directly with your existing email gateway via API or webhook, adding a visual threat intelligence layer without replacing your current tools. For financial institutions already managing payment fraud through banking fraud detection systems, adding visual scanning creates a true defense in depth strategy that addresses the full spectrum of AI enhanced email attacks before they reach a human inbox.

Protect Your Inbox from Visual Fraud

Business email compromise costs organizations $2.7 billion annually. Add Sightova's visual threat layer to your email security stack and neutralize the attacks that text filters miss.