FALSE CLAIMS

IN SPAM

A report by the FTC’s Division of

Marketing Practices

April 30, 2003
1

 Studies by others have focused on the economic costs resulting from

spam (see, e.g., http://www.ferris.com (April 8, 2003)), the volume of UCE

(see, e.g., http://www.brightmail.com/pressreleases/122302_holiday_spam_alert.html (Dec. 23, 2002)), and consumer attitudes regarding spam (see, e.g.,

http://www.harrisinteractive.com/harris_poll/index.asp (Jan. 3, 2003)).

1

About 1,000

pieces of spam

were analyzed to

determine whether

they bore the hallmarks of falsity.

FTC staff

analyzed false

claims appearing

in “From” and

“Subject” lines and in

the body of

messages.

FALSE CLAIMS IN SPAM

I. OVERVIEW

In this report, staff of the Federal Trade Commission’s (“FTC”) Division

of Marketing Practices describes the results of its review of approximately

1,000 pieces of unsolicited commercial email (UCE), commonly known as

“spam.” This random sample was drawn from a pool of over 11,000,000 pieces

of spam. This study, which focuses on the likely truth or falsity of claims

contained in the messages, supplements two previous FTC studies of spam – the

“Spam Harvest” (finding that 86% of addresses posted to web pages and

newsgroups received spam) and the “Remove Me Surf” (finding that 63% of

email list removal requests were not honored).

This study represents the first extensive review of false claims appearing

in UCE.1

 FTC staff who are trained to spot deceptive and unfair practices

identified indicators of falsity for several types of offers likely to appear in

spam. These indicators of falsity were based on representations found to be

false in previous law enforcement actions brought by the Commission and on

staff research. Staff then analyzed each piece of spam to determine whether the

“From” line, “Subject” line, or message content contained any of these signs of

falsity. The presence of signs of falsity in a message reviewed in this study

does not mean that the message satisfies the legal standard of deception under

the FTC Act; further investigation would be necessary to make such a

determination. Staff also reviewed each piece of spam to determine whether the

message contained pornographic images (in order to determine whether the

nature of the images was disclosed in the “Subject” line), a request for personal

information, or a label indicating that the message was an advertisement.

The messages reviewed by FTC staff consist of random samples from

three FTC data sets – the UCE Database (consisting of spam forwarded to the

FTC by members of the public), the Harvest Database (consisting of messages

received by undercover FTC email boxes seeded on Internet web pages and in

chat rooms), and spam received by FTC employees in their official FTC

inboxes. A full description of the data sets, the sampling ratios, and likely

biases of each data set are discussed in Section XI. (Methodology).
2

Investment/

Business

Opportunity

offers account for

20% of spam

studied. The

majority of these are

work-at-home,

franchise, chain

letter, and other nonsecurities offers.

Offers Made via Spam

Leisure/Travel

2% Education

1% Computers/Internet

7%

Other

9%

Health

10%

Investment/ 

Business 

Opportunity

20%

Adult

18%

Finance

17%

Products/Services

16%

Investment/

Business

Opportunity,

Adult, and Finance

offers together

comprise over half of

spam in sample.

II. TYPES OF OFFERS MADE VIA SPAM

FTC staff began its analysis by determining the type of offer being made

in each spam message. The messages fell into eight general categories, with a

catch-all category included for types of offers that appeared infrequently:

Type of Offer Description

Investment/Business Opportunity work-at-home, franchise, chain letters, etc.

Adult pornography, dating services, etc.

Finance credit cards, refinancing, insurance, foreign

money offers, etc.

Products/Services products and services, other than those coded

with greater specificity.

Health dietary supplements, disease prevention,

organ enlargement, etc.

Computers/Internet web hosting, domain name registration, email

marketing, etc.

Leisure/Travel vacation properties, etc.

Education diplomas, job training, etc.

Other catch-all for types of offers not captured by

specific categories listed above. 

The following illustration sets forth the prevalence of different types of

offers in the random sample of spam analyzed by FTC staff:
3

Only 7% of spam

analyzed

concerned

Computer or Internetrelated goods or

services.

Percentage of Spam with False “From” Line

Yes

33%

No

67%

Thirty-three

percent of spam

analyzed

contained false

information in the

“From” line.

Together, Investment/Business Opportunity, Adult, and Finance offers

comprised 55% of the random sample of spam analyzed by FTC staff. 

Surprisingly, given that UCE inherently targets consumers with computers and

Internet connections, only 7% of the spam analyzed concerned offers for

computer or Internet-related products or services. 

III. FALSITY IN “FROM” LINE

The “From” line in each UCE message was examined to determine

whether the information obscured the true identity of the sender. FTC staff

determined whether the “From” line contained any of the following indicators

of falsity:

Type of “From”

Line Falsity

Description

Blank Sender’s identity has been stripped from “From” line

Connotes Business

Relationship

Name of sender suggests a business relationship between sender

and recipient (e.g., “youraccount@vendorxyz.com”)

Connotes Personal

Relationship

Name of sender suggests a personal relationship between sender

and recipient (e.g., use of first name only, which may suggest that

the message is from someone in the recipient’s address book.)

Message from

Recipient

Sender’s identifying information has been stripped from message

and replaced with recipient’s email address

Disguised in Other

Way

Catch-all for other methods used to disguise the sender’s true

email address (e.g., sender, as identified in the message text, uses

another person or entity’s name or email address in the from line)

One-third of the spam messages contained false information in the

“From” line.
4

Types of False Claims in “From” Line

Personal 

Relationship

46%

Business 

Relationship

13%

Message from 

Recipient

3%

Blank

14%

Disguised Identity 

of Sender in Some 

Other Way

24%

Of the spam

containing false

information in the

“From” line, 46%

suggested a personal

relationship between

the sender and

recipient.

Percentage of Spam with False “From” Line 

by Type of Offer

28% 30% 27%

34% 30% 31%

46%

33%

43%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Adult Computers/

Internet

Education Finance Health Investment/

Bus. Op.

Leisure/

Travel

Other Products/

Services

Senders of all

types of spam

analyzed

frequently obscure

their identities in the

“From” line. 

Of the messages containing indicators of falsity in the “From” line,

nearly half claimed to be from someone with a personal relationship with the

recipient. Such a personal relationship was typically manifested by the use of

only a first name in the “From” line, suggesting that the message was coming

from someone whose name was in the recipient’s email address book.

“From” lines with signs of falsity appeared in UCE for all types of offers, with

incidence rates ranging from a low of 27.2% for education-related spam to a

high of 45.8% for spam coded as “Other,” and 43.1% for finance-related spam. 

No matter the type of offer contained in the UCE, senders of the UCE reviewed

by FTC staff frequently obscured their identity by manipulating the information

in the “From” line.
5

Twenty-two

percent of spam

analyzed contained

false information in the

“Subject” line. 

Percentage of Spam with False “Subject” Line

No

78%

Yes

22%

IV. FALSITY IN “SUBJECT” LINE

FTC staff examined the “Subject” line in each spam message in the

sample to determine whether the information appeared to be false. “Subject”

lines were analyzed to determine whether they contained any of the following

characteristics:

Type of Subject Line

Falsity

Description

Blank Contains no information about the subject of the message

Connotes Business Relationship Suggests existence of business relationship between

sender and recipient (e.g., “your order’s status”)

Connotes Personal Relationship Suggests existence of personal relationship between

sender and recipient (e.g., “Bob says ‘hi’”)

Unrelated to Content of Message Content of message differs from description in “Subject”

line

Re: Suggests that the message is in reply to a message

previously sent by recipient

Other Catch-all for other methods used to disguise the true

content of the message (e.g., “Subject” line indicates that

the message is “extremely urgent.”) 

Twenty-two percent of UCE in the sample contained false information

in the “Subject” line.
6

Forty-two percent

of spam containing

misleading

“Subject” lines

misrepresented that

the sender had a

personal or business

relationship with the

recipient. 

Types of False Claims in “Subject” Line

Re:

14%

Personal 

Relationship

25%

Business 

Relationship

17%

Other

7%

Blank

5%

Misleading/ 

Unrelated

32%

Percentage of Spam with False “Subject” Line

by Type of Offer

32%

18% 20% 21% 18%

29%

11%

34% 27%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Adult Computers/

Internet

Education Finance Health Investment/

Bus. Op.

Leisure/

Travel

Other Products/

Services

One in every three

“adult” spam

messages

reviewed by the FTC

contained false

information in the

“Subject” line. 

Of the spam containing signs of falsity in their “Subject” lines, nearly

one-third contained a “Subject” line that bore no relationship to the content of

the message. These false “Subject” lines were designed to lure consumers into

opening the messages, expecting to see content related to the representations in

the “Subject” lines. Forty-two percent of the spam containing false “Subject”

lines misrepresented that the sender had a personal or business relationship with

the recipient.

While false “Subject” lines were found in all types of offers, over onethird of “adult” offers appeared to misrepresent the content of the message.
7

Percentage of Spam with 

False “From” OR “Subject” Line

Yes

44%

No

56%

Forty-four percent

of spam reviewed

by FTC staff

contained false

information in the

“From” or “Subject”

lines.

Percentage of Spam with False “From” OR “Subject” Line

by Type of Offer

42% 40%

52%

37%

54%

36%

46% 44%

53%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Adult Computers/

Internet

Education Finance Health Investment/

Bus. Op.

Leisure/

Travel

Other Products/

Services

Over half of

finance-related

spam analyzed by

the FTC contained false

“From” or “Subject”

lines.

V. FALSITY IN “FROM” OR “SUBJECT” LINES

Forty-four percent of spam analyzed by FTC staff contained hallmarks

of falsity in either the “From” line or “Subject” line.

All types of spam in the sample analyzed by FTC staff contained indicators of

falsity in the “From” or “Subject” line, with incidence rates ranging from a low

of 36.4% for education-related UCE to a high of 53.9% for finance-related

spam.
8

Percentage of Spam with False Text

Yes

40%

No

60%

Forty percent of

spam studied

contained signs of

falsity in the body of

the message.

Percentage of Spam with False Text

by Type of Offer

49%

90%

1%

10%

35%

28%

11%

32%

45%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Adult Computers/

Internet

Education Finance Health Investment/

Bus. Op.

Leisure/

Travel

Other Products/

Services

Ninety percent of

spam concerning

investment and

business opportunity

offers analyzed by the

FTC contained likely

false claims.

VI. FALSITY IN MESSAGE TEXT

Using expertise gleaned from past law enforcement actions and its own

research, FTC staff identified specific representations that were likely to be

false. Staff then analyzed each spam message in the sample to determine

whether its text bore any of the enumerated hallmarks of falsity. Approximately

40% of the messages had at least one indication of falsity.

The incidence of likely false claims in the text of spam varied

considerably among types of offers. Ninety percent of UCE in the sample that

advertised investment and business opportunities contained signs of falsity.
9

Chain letter and

effortless income

offers are

frequently marketed

through UCE.

Spotlight on:

“Chain Letter” Spam

What the “chain letters” say:

• “Read on. It’s true. Every word of it. It is legal. I 

checked.”

What to watch out for:

• Chain letters may try to win your confidence by 

claiming that they’re legal, and even that they’re 

endorsed by the government. Nothing is further from

the truth.

Of the spam

analyzed, 48%

marketing

healthcare products

and 47% marketing

travel or leisure

products contained

signs of falsity in the

text of their messages.

Many of the Investment/Business Opportunity messages analyzed for

this study could be categorized as “chain letter” messages, and many others

advertised some other form of “effortless income.”

Other topics generating a significant percentage of messages with

indicators of falsity included those involving health (48%) and leisure/travel

(47%). Common “health” spam messages advertised weight loss products and

intimacy aids; common “leisure/travel” spam messages offered prize and

vacation promotions.

VII. FALSITY IN “FROM” LINE, “SUBJECT” LINE,
10

Percentage of Spam with False 

"From" Lines, "Subject" Lines, or 

Text

Yes

66%

No

34%

Sixty-six percent

of spam analyzed

contained false

“From” lines, “Subject”

lines, or message text.

Percentage of Spam with False “From” Lines,

“Subject” Lines, OR Message Text, by Type of Offer

69%

57%

96%

42%

71%

45%

57% 54% 60%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Adult Computers/

Internet

Education Finance Health Investment/

Bus. Op.

Leisure/

Travel

Other Products/

Services

Ninety-six percent

of spam

concerning

investment and

business opportunities

contained false “From”

lines, “Subject” lines,

or message text.

OR MESSAGE TEXT

Sixty-six percent of spam analyzed by FTC staff contained indications

of falsity in their “From” lines, “Subject” lines, or message text.

All types of spam in the sample contained indications of falsity in the

“From” or “Subject” line or in the message text, with falsity rates ranging from

a low of 42% for spam involving the sale of products and services to 96% for

spam offering investment and business opportunities.
11

Two percent of the

spam analyzed

contained the

“ADV” label in the

subject line, which is

required by several

state laws. Percentage of Spam Using “ADV” in Subject Line

No

98% Yes

2%

While relatively

few spam in the

study asked the

recipient to submit

personal information,

those messages

requesting such

information typically

contained signs of

falsity.

VIII. USE OF THE “ADV:” LABEL 

IN “SUBJECT” LINES OF MESSAGES STUDIED

Several states have enacted laws in recent years requiring senders of

spam to begin every subject line with the phrase “ADV:” (an abbreviation used

to identify advertising) in messages sent to recipients of those states. FTC

staff’s study of a sample of messages found that compliance with this labeling

requirement was sparse.

IX. MESSAGES REQUESTING RECIPIENTS’ 

PERSONAL INFORMATION

The spam study showed that messages rarely requested recipients to

submit personal information in responding to the senders’ offers. In analyzing

spam regarding this feature, staff distinguished between information that is

public and readily available, such as the sender’s name and address, and

information that is not public or is not readily available, such as the sender’s

bank account number. The latter type of personal information consists of data

that can lead to identity theft or other monetary harm if it falls into the wrong

hands; the FTC advises consumers to guard this information carefully. Only 14

of the UCE in the sample requested such personal information. Ten of these 14

messages also contained indicators of falsity in the “From” line, “Subject” line,

or body of the message.
12

Spotlight on:

“Nigerian” Spam & 

Personal Information

• These messages may ask for your bank account 

number–purportedly so the sender can wire you 

millions of dollars.

• If you respond and provide your account information, 

you will receive nothing–and the sender will have 

access to funds in that account.

X. USE OF ADULT IMAGERY IN OFFERS FOR PORNOGRAPHY 

Consumers and lawmakers have repeatedly expressed concern over

sexually explicit images contained in spam, principally because the images may

be accessible to children. To help determine the scope of this issue, FTC staff

analyzed the prevalence of pornographic imagery in the Harvest Database and

the database of spam received in FTC employees’ inboxes. (Because many

consumers who forwarded their spam to the UCE Database did not send the

spam in an HTML-enabled format, the UCE Database sub-sample was excluded

from this particular analysis). A message was considered to have “adult

imagery” if the image appeared automatically (without requiring the consumer

to hyperlink to a web page) and the image contained nudity.
13

Seventeen percent

of spam

advertising

pornographic websites

included “adult

images” in the body of

the message.

Percentage of Pornographic Spam with “Adult Imagery”

“Adult Imagery” Spam with False “From” OR “Subject” Line

Truthful

59%

False

41%

No Imagery

83%

With Imagery

17%

Forty-one percent

of spam containing

“adult imagery”

contained false

information in their

“From” or “Subject”

lines.

Seventeen percent of pornographic offers in the spam analyzed by FTC

staff contained “adult imagery.” Over 40% of these pornographic spam

messages contained false statements in their “From” or “Subject” lines, making

it more likely that recipients would open the messages without knowing that

pornographic images will appear.

XI. METHODOLOGY

For this study, FTC staff analyzed UCE from three sources – the UCE

Database (approximately 450 sample messages), the Harvest Database

(approximately 450 sample messages), and spam received in official FTC

inboxes (approximately 100 sample messages). The UCE Database and Harvest

Database samples were drawn from messages received during the last six

months of 2002. The UCE messages were collected for this study using random

selection protocols established by the FTC Bureau of Economics. To enable

future internal analysis of spam not blocked by the FTC’s internal computer

systems, the data sample was supplemented with 100 pieces of randomlyselected UCE received by FTC employees during March 2003.

The UCE Database contains spam forwarded to the Commission by

members of the public. Consumers currently contribute about 130,000

messages per day to the UCE Database, and a total of 11,184,139 messages

were forwarded to the FTC’s UCE Database during the time period from which

the study’s sample was drawn. The volume of messages in the UCE Database

makes it likely that this data source provides a fairly representative look at the
14

types of messages that many consumers receive. Nonetheless, the email in the

database may be skewed because contributors are likely to be knowledgeable

about spam or have a dismal view of UCE.

The Harvest Database consists of 3,651 messages received by FTC

undercover email accounts that were established as part of its email harvesting

study. As part of the Harvest study, the FTC and its law enforcement partners

established 250 email accounts and posted these email addresses to 175

different locations on the Internet. Specific email addresses were posted on

newsgroups, message boards, chat rooms, instant messaging services, email

service directories, web pages, domain name “whois” information, online

resume services, and online dating services. FTC staff then tracked email

received by each of the 250 email accounts. 

While spam contained in the Harvest Database does not suffer from the

same potential “contributor” biases as the UCE Database, it may not be fairly

representative of the range of spam offers that consumers receive. The database

contains messages sent by marketers who use harvesting programs to obtain

email addresses. Many marketers eschew using harvesting programs and obtain

email address lists in other fashions.

The internal FTC spam database may suffer from the same potential

biases as the UCE Database. Commission staff voluntarily contributed the

spam they received in their FTC inboxes for analyses. Contributors may be

those employees most annoyed with spam. Moreover, the FTC employs email

filtering mechanisms that likely affect the representativeness of this sample. 

To overcome the potential biases in each of these data sets, the data was

combined into a single database. The study’s results provide a snapshot of

approximately 1,000 pieces of spam drawn from a variety of sources available

to FTC staff. It is unknown whether a random sample of all spam sent in the

stream of commerce would yield the same findings.

XII. CONCLUSION

This study represents a snapshot of spam, as viewed through random

samples of three data sets available to FTC staff. Because all vehicles of

commerce, including spam, are in constant motion, this snapshot may not

provide a complete picture of the incidence of false claims in spam.

Reviewing this snapshot, FTC staff found that UCE for Investment/

Business Opportunity, Financial, and Adult offers accounted for over half of all

messages. When analyzing the prevalence of false claims, FTC staff found

indicators of falsity in the “From” lines, “Subject” lines, or content of two-
15

thirds of the messages. Furthermore, this study found that the use of the “adv”

(advertising) label by senders of spam was almost non-existent. Finally, the

study found that 41% of spam depicting nudity contained indicators of falsity in

their “From” or “Subject” lines.

Future studies should be designed to identify changes in the types of

offers being made through spam and the frequency of signs of falsity appearing

in the “From” lines, “Subject” lines, and content of UCE.