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Current Mean TTE
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Zero-Day Rate
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CVE-Exploit Pairs
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Model R-Squared
exponential decay fit

TTE Metrics Comparison

Three different TTE calculations based on exploit source types

TTE
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Median Time-to-Exploit
Mean: --
Sources: CISA KEV, VulnCheck KEV, Shadowserver
-- pairs
TTZDE
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Median TTE + Zero-Day Sources
Mean: --
Sources: TTE + Google 0-Day, ZDI
-- pairs
TTEP
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Median TTE + PoC Sources
Mean: --
Sources: TTE + GitHub PoC
-- pairs
Note: TTE uses confirmed exploitation sources. TTZDE includes zero-day tracking (often negative values indicating exploitation before disclosure). TTEP includes PoC availability (typically higher values as PoCs are created after disclosure).

From Vulnerability to Exploitation

TTE (Time-to-Exploit) measures the gap between CVE disclosure and confirmed exploitation

Metric:
Exploits (count) Median Mean
Based on CVE-exploit pairs from trusted sources (CISA KEV, VulnCheck KEV & Shadowserver)

TTE Metrics Comparison Over Time

Comparing median TTE across different exploit source combinations

TTE (KEV+Shadowserver) TTZDE (+Zero-Day) TTEP (+PoC)
TTE: Confirmed exploitation (KEV + Shadowserver) | TTZDE: Includes zero-day tracking sources (negative = exploited before disclosure) | TTEP: Includes PoC availability (higher values as PoCs created after disclosure)

Zero-Day Rate

% of exploited CVEs where exploitation occurred before or on disclosure day (TTE ≤ 0)

Exploit Rate

% of all published CVEs confirmed exploited in the wild, versus total CVE volume

Time-to-Exploit Milestones

When mean time-to-exploit crosses each threshold

TTE Methodology

How Phoenix Security computes Time-to-Exploit, based on the zerodayclock.com methodology.

What is TTE?

Time-to-Exploit (TTE) measures the elapsed time between when a vulnerability is publicly disclosed and when a confirmed exploit becomes available. A negative TTE means the vulnerability was exploited before public disclosure - a true zero-day.

TTE = (t_exploit - t_disclosure) / 24 - measured in days

Three TTE Metrics

We compute three different TTE metrics based on different exploit source combinations to provide a comprehensive view:

TTE (Time-to-Exploit)

Sources: CISA KEV, VulnCheck KEV, Shadowserver

What it measures: Confirmed in-the-wild exploitation. This is the primary metric showing when vulnerabilities are actually being exploited by attackers. Uses honeypot data (Shadowserver) and official KEV catalogs.

Interpretation: Lower values indicate faster weaponization. Negative values indicate zero-days.

TTZDE (TTE + Zero-Day Sources)

Sources: TTE + Google Project Zero, ZDI Advisories

What it measures: Includes zero-day tracking programs that specifically monitor vulnerabilities exploited before disclosure. ZDI and Google 0-Day track ITW (in-the-wild) zero-days.

Interpretation: Often shows negative median values because these sources focus on zero-days. Higher zero-day rate than TTE.

TTEP (TTE + PoC Sources)

Sources: TTE + GitHub PoC repositories

What it measures: Exploit availability rather than confirmed exploitation. GitHub PoCs represent when exploit code becomes publicly available, which may be before or after actual attacks.

Interpretation: Typically shows higher values than TTE because PoCs are often created after CVE disclosure. Lower zero-day rate.

Corruption Filtering

Even trusted sources contain data artifacts. Before computing TTE, we apply two filters:

  • Pre-2010 timestamps dropped. Exploit dates before 2010-01-01 are database defaults (epoch, year 0001) rather than real observations.
  • TTE less than -180 days dropped. When a CVE is retroactively assigned to a vulnerability that was exploited years earlier, it produces an artificially extreme negative TTE. We cap at -180 days to remove these while preserving real zero-day campaigns (typically -30 to -90 days).

Statistical Approach

After filtering, TTE values are grouped by year and two central tendency measures are computed:

  • Median TTE: The middle value when all TTE values for a year are sorted. Robust against outliers but can be insensitive to real shifts in the tails of the distribution.
  • 10% Trimmed Mean: Sort all TTE values, remove the bottom 5% and top 5%, then average the remaining 90%. This reduces the impact of extreme outliers while remaining more sensitive to real trends than the median.

Zero-Day Classification & Prediction Model

  • Zero-day: When TTE <= 0 (exploit predates or matches disclosure), the CVE is classified as a zero-day.
  • Zero-Day Rate: Percentage of exploited CVEs that are zero-days. Calculated as zero_day_count / total_exploited * 100
  • Exploit Rate: Percentage of all published CVEs that are confirmed exploited. Calculated as exploited_count / total_cves_published * 100
  • Prediction model: An exponential decay function TTE(year) = a * e^(-b*(year-2018)) is fit to yearly median TTEs using least-squares regression. This model projects when mean TTE will cross one-week, one-day, one-hour, and one-minute thresholds.

Data Sources

CISA KEV
Confirmed in-the-wild exploitation
Field: dateAdded
VulnCheck KEV
Extended exploitation intelligence
Field: date_added
Shadowserver
Honeypot exploitation detection
Field: first_seen
Google Project Zero
ITW zero-day tracking
Field: date_patched
ZDI Advisories
Zero-day disclosures
Field: published
GitHub PoCs
Exploit availability
Field: created_at

Understanding the Values

Value Meaning Risk Level
TTE < 0 Zero-day: Exploited before public disclosure Critical
TTE = 0-7d N-day: Exploited within first week High
TTE = 7-30d Rapid exploitation within first month Medium
TTE > 30d Long-tail: Exploitation after first month Lower
Methodology inspired by zerodayclock.com | Data powered by Phoenix Security
-- Median TTE
-- Mean TTE
-- Zero-Days
-- In KEV
-- GitHub PoCs
-- Critical
CISA KEV VulnCheck KEV GitHub PoC Metasploit Nuclei Zero-Day
Exploited Vulnerabilities Loading...
CVE / Product Published First Sighting CVSS Severity TTE Sources Intel
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CVE / Product Disclosure CVSS Source Vendor Details