Cyberloq Technologies (CLOQ) Total Liabilities (2011 - 2026)
Cyberloq Technologies (CLOQ) recorded Total Liabilities of $4.64 million in Q2 2026, up 29.2% from $3.59 million a year earlier and up 9.4% from the prior quarter.
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Analysis
Cyberloq Technologies (CLOQ) Total Liabilities (2011 - 2026) Analysis & Trends
At the end of FY2025, Cyberloq Technologies reported Total Liabilities of $4.19 million, up 48.0% from FY2024.
- Annual Total Liabilities has increased for four straight years, with a five-year compound annual growth rate of 65.5% (FY2020 to FY2025).
- Across earlier years, Total Liabilities came in at $2.83 million in FY2024 (+177.2%), $1.02 million in FY2023 (+215.1%), $324,132 in FY2022 (+8.2%) and $299,530 in FY2021 (-11.2%).
- The Q2 2026 figure is the highest quarterly Total Liabilities in data going back to Q4 2011.
- On a year-over-year basis, Total Liabilities has increased for 12 consecutive quarters, with growth averaging 107.7% over the last eight quarters.
- Peak year-over-year performance for Total Liabilities in the last five years was growth of 343.8% in Q2 2024, against a decline of 59.7% in Q1 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $4.24 million (Q1 2026), $4.19 million (Q4 2025) and $3.76 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 319.55 Bn | 304.63 Bn | 2.30 Bn | 20.97 Bn |
| 2 | CrowdStrike Holdings | 265.46 Bn | 245.90 Bn | 1.10 Bn | 6.89 Bn |
| 3 | Fortinet | 129.36 Bn | 115.29 Bn | 1.64 Bn | 9.31 Bn |
| 4 | Snowflake | 115.65 Bn | 102.97 Bn | 1.04 Bn | 6.54 Bn |
| 5 | Datadog | 96.45 Bn | 78.09 Bn | 881.34 Mn | 3.18 Bn |
| 6 | Axon Enterprise | 34.50 Bn | 29.03 Bn | 546.45 Mn | 3.81 Bn |
| 7 | Okta | 33.79 Bn | 23.89 Bn | 641.00 Mn | 2.17 Bn |
| 8 | Zscaler | 32.51 Bn | 18.63 Bn | - | 5.27 Bn |
| 9 | Baidu | 29.59 Bn | -44.04 Bn | 1.47 Mn | 27.69 Bn |
| 10 | Cyberloq Technologies | 25.44 Mn | 25.01 Mn | - | 4.64 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 4.64 Mn |
| Mar 31, 2026 | 4.24 Mn |
| Dec 31, 2025 | 4.19 Mn |
| Sep 30, 2025 | 3.76 Mn |
| Jun 30, 2025 | 3.59 Mn |
| Mar 31, 2025 | 2.93 Mn |
| Dec 31, 2024 | 2.83 Mn |
| Sep 30, 2024 | 2.50 Mn |
| Jun 30, 2024 | 2.13 Mn |
| Mar 31, 2024 | 1.04 Mn |
| Dec 31, 2023 | 1.02 Mn |
| Sep 30, 2023 | 689,592.00 |
| Jun 30, 2023 | 479,191.00 |
| Mar 31, 2023 | 375,479.00 |
| Dec 31, 2022 | 324,132.00 |
| Sep 30, 2022 | 353,878.00 |
| Jun 30, 2022 | 859,308.00 |
| Mar 31, 2022 | 931,744.00 |
| Dec 31, 2021 | 299,530.00 |
| Sep 30, 2021 | 322,048.00 |
API Access
Cyberloq Technologies Total Liabilities API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=total-liabilities&ticker=CLOQ&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "CLOQ", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=total-liabilities&ticker=CLOQ&period=max&api_key=YOUR_API_KEY");
const data = await res.json();