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L3HARRIS Technologies, Inc.: current liabilities

L3HARRIS Technologies current liabilities: $7.23 billion at 2026-01-02, down 5.3% on the year. 18 values since 2009 from SEC filings, each linked to its filing.

All L3HARRIS Technologies, Inc. financial histories

At a glance

L3HARRIS Technologies reported current liabilities of $7.23 billion at 2026-01-02, down 5.3% from $7.63 billion a year earlier. From 2009 to 2026 it grew at a compound 12.0% a year, from $1.11 billion to $7.23 billion. Across the last five reported years it ranged from $4.55 billion (2021-12-31) to $8.00 billion (2023-12-29). That was 17.5% of total assets ($41.2 billion) at the same date.

Computed from the values in the table below, in USD; each links to the filing it came from.

What this measure means

Obligations classified as current under the operating-cycle or one-year boundary. The balance includes more than short-term borrowing.

Exact concept: us-gaap:LiabilitiesCurrent. Each value is a balance at the reporting date, not a flow earned over a year. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2009-07-03 to 2026-01-02. The SEC response was captured on 2026-09-19.

Selected filing history

Current liabilities in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
-2026-01-027,226,000,000USD2026-02-1210-K · 0000202058-26-000015 SEC
-2025-01-037,633,000,000USD2026-02-1210-K · 0000202058-26-000015 SEC
-2023-12-298,004,000,000USD2025-02-1410-K · 0000202058-25-000023 SEC
-2022-12-305,776,000,000USD2024-02-2010-K · 0000202058-24-000029 SEC
-2021-12-314,551,000,000USD2023-02-2410-K · 0000202058-23-000014 SEC
-2021-01-014,240,000,000USD2022-02-2510-K · 0000202058-22-000015 SEC
-2020-01-034,009,000,000USD2021-03-0110-K · 0000202058-21-000008 SEC
-2019-06-282,268,000,000USD2019-08-2210-K · 0000202058-19-000090 SEC
-2018-06-291,850,000,000USD2019-08-2210-K · 0000202058-19-000090 SEC
-2017-06-301,967,000,000USD2019-08-2210-K · 0000202058-19-000090 SEC
-2016-07-011,981,000,000USD2017-08-2910-K · 0000202058-17-000037 SEC
-2015-07-032,274,000,000USD2016-08-2910-K · 0000202058-16-000022 SEC
-2014-06-271,115,000,000USD2015-08-3110-K · 0001193125-15-308363 SEC
-2013-06-281,297,400,000USD2014-08-2510-K · 0001193125-14-320240 SEC
-2012-06-291,414,400,000USD2013-08-2610-K · 0001193125-13-346761 SEC
-2011-07-011,430,500,000USD2012-08-2710-K · 0001193125-12-369967 SEC
-2010-07-021,051,800,000USD2011-08-2910-K · 0000950123-11-081041 SEC
-2009-07-031,109,700,000USD2010-08-3010-K · 0000950123-10-082207 SEC

Related L3HARRIS TECHNOLOGIES, INC. histories

All 62 L3HARRIS Technologies histories

Inspect the source

Entity
L3HARRIS TECHNOLOGIES, INC. / CIK 0000202058
Captured
SEC response SHA-256
42fd17c34242f68b8fcd3bed7c20bd186d8d39249e8e4d915414899a805ec753

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.

Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.

Use this in research

A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.

These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.

Research methodology · Execution and cost assumptions · Check backtest overfitting

Build with the open-source tools

Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.

The MCP server is free and MIT-licensed: npx -y canli-mcp. If these records help your research, a star on GitHub helps other researchers find them.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0000202058.json") as response:
    record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
    print(concept["tag"], next(iter(concept["observations"])))